The DOI matches its Crossref record; 182 of the 185 references it cites were found in a registry or an index; 69 of the 269 sources its claims cite were checked for support.
Algorithms as work designers: How algorithmic management influences the design of jobs
Open accessAbstract
Abstract We review the literature on algorithmic management (AM) to bridge the gap between this emerging research area and the well-established theory and research on work design. First, we identify six management functions that algorithms are currently able to perform: monitoring, goal setting, performance management, scheduling, compensation, and job termination. Second, we show how each AM function affects key job resources (e.g., job autonomy, job complexity) and key job demands (e.g., workload, physical demands); with each of these resources and demands being important drivers of worker motivation and their well-being. Third, rejecting a deterministic perspective and drawing on sociotechnical systems theory, we outline key categories of variables that moderate the link between AM on work design, namely transparency, fairness and human influence (e.g., whether workers can control the system). We summarize our review in the form of a model to help guide research on AM, and to support practitioners and designers in the creation and maintenance of meaningful jobs in the era of algorithms.
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Claims the paper makes
42 Partly supported · 33 Own interpretation · 32 No full text of the sources · 25 Not checked yet · 24 Sources not found · 19 No basis given · 7 Supported so far · 3 Couldn’t confirm · 2 Supported · 1 Not supported · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“In gig work, the algorithmic task allocation process is highly contingent on demand or customer satisfaction scores (Gerber & Krzywdzinski, 2019;Gregory, 2020;Griesbach et al., 2019).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic goal setting.
What the sources say
- Partly supportedcites Gerber & Krzywdzinski, 2019 sourceExperimental — accuracy not yet measured
The Microtask platforms section (pp. 21–22) says algorithmically organised rankings help allocate tasks and draw on ratings of completed jobs, including client ratings. The paper does not establish that allocation is contingent on demand, and it describes other factors besides customer ratings, including experience and activity (p. 21; Discussion and Conclusions, p. 33). Its findings concern crowdwork platforms, not gig work generally. (LLM, conf=0.86)
- Not matchedcites Gregory, 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Griesbach et al., 2019 source
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Descriptive algorithms are likely to reinvent the world of performance management (PM) in multiplying the metrics available to precisely quantify various facets of employees' actions, emotions, performance, behaviors, attitudes and physical state (Angrave et al., 2016;Tambe et al., 2019), but also customer-related information such as satisfaction and traffic (Evans & Kitchin, 2018;Levy & Barocas,”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic performance management.
What the sources say
- Partly supportedcites Angrave et al., 2016 sourceExperimental — accuracy not yet measured
In ‘Defining big data and HR analytics’ (pp. 5–6), the paper describes existing employee performance and attitude data and the possibility of using digital records to infer mood, morale and activity. It does not establish that descriptive algorithms will precisely quantify employees’ physical state or reinvent performance management; it also says the means of integrating and analysing the larger data sources are not yet well established. The customer-related clause is attached to other citations, not Angrave et al. (LLM, conf=0.86)
- Not checked — no full text of the sourcecites Tambe et al., 2019 source
- Partly supportedcites Evans & Kitchin, 2018 sourceExperimental — accuracy not yet measured
The Conclusion (page unavailable) says customer satisfaction is delegated to big-data and algorithmic processing. The section “Non-coded activities and symbolic labour” (page unavailable) describes a running count of customers passing through the self-scan area, supporting the traffic example. The paper does not establish that descriptive algorithms will multiply metrics that precisely quantify customer satisfaction and traffic. (LLM, conf=0.84)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“with each of these resources and demands being important drivers of worker motivation and their well-being.”
- Also stated in: § THE EFFECT OF ALGORITHMIC MANAGEMENT ON WORK DESIGN · boosted
“Considerable evidence links job resources and job demands with workers' motivation, well-being and performance (for meta-analyses or reviews, see: Humphrey et al., 2007;Knight & Parker, 2021;Parker & Ohly, 2008).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Abstract
What the sources say
- Not checked — no full text of the sourcecites Humphrey et al., 2007 source
- Partly supportedcites Knight & Parker, 2021 sourceExperimental — accuracy not yet measured
In “Work design theories and performance” (page unavailable), the paper says job characteristics affect motivation and performance. Its discussion of the Job-Demands Resources model (page unavailable) links resources and demands to strain, well-being, and subsequent performance. It does not establish the citing sentence’s more specific implication that demands, as well as resources, drive worker motivation. (LLM, conf=0.82)
- Not checked — no full text of the sourcecites Parker & Ohly, 2008 source
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § THE EFFECT OF ALGORITHMIC MANAGEMENT ON WORK DESIGN · boosted
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The impact of the use of AM to set goals on the reduction of workers' autonomy has been outlined by many scholars, namely in gig-work where autonomy in task selection is often viewed by externals as a major advantage of platform-based work (Curchod, Patriotta, Cohen, & Neysen, 2019;Gerber & Krzywdzinski, 2019;Griesbach et al., 2019;Rosenblat, 2018;Shapiro, 2018).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic goal setting.
What the sources say
- Partly supportedcites Curchod et al., 2019 sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
- Partly supportedcites Gerber & Krzywdzinski, 2019 sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
- Not checked — no full text of the sourcecites Griesbach et al., 2019 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“AI-driven algorithmic monitoring thus allows to collect and record a vast array of new information and metrics, such as emotions (Chan, 2018;Pinheiro, Ramos, Donizete, Picanço, & De Oliveira, 2017), movements, sleep time, physical and health condition, social media activity, internet browser history (Angrave, Charlwood, Kirkpatrick, Lawrence, & Stuart, 2016;Leicht-Deobald et al., 2019)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic monitoring.
What the sources say
- Not matchedcites Chan, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Partly supportedcites Angrave et al., 2016 sourceExperimental — accuracy not yet measured
In “Defining big data and HR analytics” (pp. 5–6), the paper describes worker data already held in HR systems and the potential to combine it with location, communications and internet-browsing data. This supports the broad point that analytics can draw on many worker metrics, including movement and browsing history. It does not identify sleep time or physical health as monitored metrics, and presents integration of the newer data sources as a possibility rather than an established capability. (LLM, conf=0.86)
- Partly supportedcites Leicht-Deobald et al., 2019 sourceExperimental — accuracy not yet measured
In “A Brief History of Algorithm-Based HR Decision-Making” (page unavailable), the paper describes monitoring location, health and fitness data, Facebook activity, and browser histories, supporting the claim that algorithmic tools can collect varied new information about workers. It does not identify sleep time as a monitored metric, so that item in the citing sentence is unsupported by our copy. (LLM, conf=0.86)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Some studies have described how these metrics can play a central role (if not the entire role) in the performance management process of both traditional workers (Bakewell et al., 2018;Dhir & Chhabra, 2019;Evans & Kitchin, 2018;Kirven, 2018;Levy & Barocas, 2018) and gig workers (Gerber & Krzywdzinski, 2019).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic performance management.
What the sources say
- Supportedcites Bakewell et al., 2018 source
The ‘See Your Team’ section (page not supplied) says the apps were interwoven with the employer’s performance-monitoring processes and introduced indicators of productivity and quality. ‘Being Monitored and Monitoring Others’ adds that tracked data were used to assess field engineers’ work, supporting a central role for metrics in this traditional workplace. (LLM, conf=0.88)
- Not checked — no full text of the sourcecites Dhir & Chhabra, 2019 source
- Supportedcites Evans & Kitchin, 2018 source
The Conclusion says retail managers’ work is directed by auto-generated KPIs and that management of work is increasingly mediated, monitored and regulated by code and data. The discussion of discipline and control also describes software-based monitoring as part of everyday performance management in retail. These passages support a central role for algorithmic metrics in managing traditional retail workers. (LLM, conf=0.91)
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Third, rejecting a deterministic perspective and drawing on sociotechnical systems theory, we outline key categories of variables that moderate the link between AM on work design, namely transparency, fairness and human influence (e.g., whether workers can control the system).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Abstract
What the sources say
- Not matchedcites Emery & Trist, 1978
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Partly supportedcites Makarius et al., 2020 sourceExperimental — accuracy not yet measured
Section 4.2 discusses how AI can change job design and identifies employee autonomy as important; section 2.1 discusses fair and transparent AI as ways to mitigate bias. But the paper does not identify transparency, fairness, and human influence as moderators of a link between algorithmic management and work design. The cited sentence presents that specific framework as the citing authors’ own outline. (LLM, conf=0.84)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Mainly found in the gig economy, this procedure starts with the platform notifying a worker of unsatisfying ratings and probability of account deactivation if no improvement, followed by official account deactivation (Gerber & Krzywdzinski, 2019;Griesbach et al., 2019;Rosenblat & Stark, 2016).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic job termination.
What the sources say
- Partly supportedcites Gerber & Krzywdzinski, 2019 sourceExperimental — accuracy not yet measured
The Microtask platforms section (p. 22) says low ratings can limit access to work until a worker sees no jobs on the dashboard. It does not describe the claimed termination procedure: a warning about ratings and possible deactivation, followed by official account deactivation. (LLM, conf=0.85)
- Not checked — no full text of the sourcecites Griesbach et al., 2019 source
- Not matchedcites Rosenblat & Stark, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Second, if not taking or implementing the termination decision, algorithms may facilitate employees' dismissal through the prediction of employee behaviors such as departure (Punnose & Ajit, 2016;Rosenbaum, 2019;Sajjadiani et al., 2019;Sikaroudi, Mohammad, Ghousi, & Sikaroudi, 2015;Zhao, Hryniewicki, Cheng, Fu, & Zhu, 2018), performance (Edwards & Edwards, 2019;Greenfield, 2018;Sajjadiani et al.,”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic job termination.
What the sources say
- Supportedcites Punnose & Ajit, 2016 source
The citation is attached to the prediction of employee departure, not to performance or fraud. The Introduction (p. 1) says organizations use machine learning to predict employees’ risk of attrition, and the paper reports a comparison of algorithms for predicting turnover. It does not establish that those predictions are used to dismiss employees, but that is the citing authors’ framing rather than the specific point attributed to this source. (LLM, conf=0.92)
- Not matchedcites Rosenbaum, 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Sajjadiani et al., 2019 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“Second, depending on the organization's strategy, it can render compensation more contingent on customer satisfaction, given the increasing role of customers in performance ratings (Wood et al., 2019).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic compensation.
What the sources say
- Supportedcites Wood et al., 2019 source
In Findings and discussion, the paper says clients rate workers and that platform algorithms direct more work to those with better scores while filtering work away from those with low ratings. Its Worker power and competition section links reputation and algorithmic ranking to income, supporting the claim that earnings can depend on customer evaluations through access to work. The paper does not describe ratings changing the payment for an individual task. (LLM, conf=0.86)
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
- Probably not a substantial claim. 54
- It may state two separate claims as one. 45
At least one cited source doesn’t support this claim or points to a different paper, and none confirmed it — see the verdicts below.
In the paper
“Social support (-)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Disputedcites Uhde et al. (2020) sourceExperimental — accuracy not yet measured
In “Data souvereignity and transparency” (page unavailable), the paper says that algorithmic scheduling systems, if designed correctly, can facilitate pro-social behavior and may benefit team climate. It does not report a negative association with social support; its discussion points in the opposite direction. (LLM, conf=0.78)
Checked by a reasoning model — may be wrong.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Disputed
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“A similar consequence of narrow algorithmic monitoring systems is a greater emphasis on quantified work objectives at the expense of other and potentially meaningful aspects of one's job (Schafheitle et al., 2020), reducing the autonomy of workers in the choice of their work methods (Day, Paquet, Scott, & Hambley, 2012;Wang, Liu, & Parker, 2020)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic monitoring.
What the sources say
- Partly supportedcites Schafheitle et al., 2020 sourceExperimental — accuracy not yet measured
In “Framework on Datafication Technology Control Configurations” (page not provided), the paper describes technology that tracks employee outputs against performance targets. It does not say that narrow monitoring increases emphasis on quantified objectives at the expense of other meaningful aspects of work. The autonomy clause is cited to different sources, so it is not judged here. (LLM, conf=0.82)
- Not checked — no full text of the sourcecites Day et al., 2012 source
- Supportedcites Wang et al., 2020 source
The Wang et al. citation is attached to the claim that monitoring reduces workers’ autonomy in choosing work methods, not to the preceding claim about quantified objectives. In “Managerial control-induced decreases in autonomy,” the paper reports that exposure to monitoring reduces employees’ control over work methods, among other aspects of their work. (LLM, conf=0.92)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Algorithmic task allocation is largely found in the gig economy and platform work (Gerber & Krzywdzinski, 2019;Lee et al., 2015;Rosenblat, 2018), and in traditional work sectors like telecommunication (Leclercq-Vandelannoitte, 2017), electronics (Gershgorn, 2015;Hitachi, 2015), public transports (Hodson, 2014), and parcel delivery (Stevens, 2015).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic goal setting.
What the sources say
- Supportedcites Gerber & Krzywdzinski, 2019 source
The Gerber and Krzywdzinski citation is attached to the gig-economy and platform-work part of the sentence, not the list of traditional sectors. The Introduction (p. 3) describes platform coordination of task allocation, and “Crowdwork as a new work model” (p. 6) explains how platforms allocate tasks using information they collect. The Discussion (p. 33) further describes algorithms regulating access to tasks. (LLM, conf=0.88)
- Not checked — no full text of the sourcecites Lee et al., 2015 source
- Not checked — no full text of the sourcecites Rosenblat, 2018
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“However, recent reviews and conceptualizations (Kellogg et al., 2019;Mateescu & Nguyen, 2019a;Schafheitle et al., 2020) consider algorithmic management as a technological phenomenon that is not contingent on the type of organization and can be found in a large array of work contexts.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic management and its functions
What the sources say
- Not checked — no full text of the sourcecites Kellogg et al., 2019 source
- Not matchedcites Mateescu & Nguyen, 2019a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Partly supportedcites Schafheitle et al., 2020 sourceExperimental — accuracy not yet measured
The Introduction (page unavailable in our copy) presents datafication technologies as applicable to both easily automated tasks and “thinking work,” supporting the claim that technology-based control spans varied work contexts. The paper discusses algorithmic decision-making in organizational control, but the passages do not establish that algorithmic management is independent of organization type. (LLM, conf=0.78)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Because data collected through monitoring devices is often used to assess their performance, workers sometimes tend to”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic monitoring.
What the sources say
- Partly supportedcites Evans & Kitchin, 2018 sourceExperimental — accuracy not yet measured
The ‘Working for data’ section says PDA-directed work is measured through system data and leaves little room for customer interaction. ‘Non-coded activities and symbolic labour’ says customer service is not captured in performance metrics, but it does not show workers choosing to evade unmonitored tasks; it says pickers must assist customers when asked. The claimed reduction in task variety is therefore supported only indirectly. (LLM, conf=0.86)
- Partly supportedcites Schafheitle et al., 2020 sourceExperimental — accuracy not yet measured
The Framework on Datafication Technology Control Configurations section describes sensor and GPS data linked to individual performance management at UPS; the ORION discussion also considers how those data might be used to rank drivers. Neither passage says workers focus on monitored tasks, evade unmonitored ones, or experience reduced task variety. Page numbers are unavailable in our copy. (LLM, conf=0.83)
- Not checked — no full text of the sourcecites Tomczak et al., 2018 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“In sum, AI algorithms, largely powered by machine learning, differ from previous automated decision-making devices in their high level of autonomy (requiring little human input), their self-learning capacities, their potential for interconnectedness, and their ability to handle massive and heterogeneous data in order to perform description, prediction, and prescription tasks (Makarius et al., 2020”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > ALGORITHMS AND THE FUNCTIONS OF MANAGEMENT THEY PERFORM
What the sources say
- Partly supportedcites Makarius et al., 2020 sourceExperimental — accuracy not yet measured
Section 2 contrasts AI with earlier task automation and identifies learning and decision-making as distinguishing features. Section 3 describes autonomous systems that can learn from data without human input, while Section 5 discusses big-data inputs and data sharing. The copy does not establish the claimed ability to handle heterogeneous data or the full description–prediction–prescription task range; page numbers were not available. (LLM, conf=0.84)
- Partly supportedcites Murray et al., 2020 sourceExperimental — accuracy not yet measured
The ‘Conjoined Agency with Automating Technologies’ section (page unavailable) says these technologies process large amounts of unstructured data, learn continuously, and select actions without human intervention, supporting most of the comparison. The cited paper does not establish interconnectedness as a distinguishing feature or present description, prediction, and prescription as a set of tasks. (LLM, conf=0.85)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“This can occur through direct scheduling decisions (Uhde, Schlicker, Wallach, & Hassenzahl, 2020), or through scheduling nudging, particularly common in gig work (Gal et al., 2020;Mateescu & Nguyen, 2019a).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic scheduling.
What the sources say
- Supportedcites Uhde, Schlicker, Wallach, & Hassenzahl, 2020 source
The citation to Uhde et al. is attached to direct scheduling decisions, not scheduling nudging. In the Procedural Justice section (page not supplied), healthcare workers describe being assigned shifts without being asked or informed, supporting the claim that direct scheduling decisions can limit workers’ voice. (LLM, conf=0.92)
- Not checked — no full text of the sourcecites Gal et al., 2020 source
- Not matchedcites Mateescu & Nguyen, 2019a
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“The strong impact of these ratings, largely questioned about their volatility, the reliability and validity (Gerber & Krzywdzinski, 2019;Greenwood, Adjerid, & Angst, 2019;Luca & Zervas, 2016;Orlikowski & Scott, 2013;Rosenblat, Levy, Barocas, & Hwang, 2017), has been associated with workers' perception of job insecurity (Curchod et al., 2019;Veen et al., 2019).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic performance management.
What the sources say
- Supportedcites Gerber & Krzywdzinski, 2019 source
The Microtask platforms section (p. 22) says client ratings can be subjective or fail to assess work quality accurately. The Macrotask platforms section (p. 25) adds that client ratings can be biased and depend on circumstances such as mood, supporting concerns about their consistency and validity. (LLM, conf=0.86)
- Partly supportedcites Greenwood, Adjerid, & Angst, 2019 sourceExperimental — accuracy not yet measured
The Related Literature section (page unavailable) discusses selection and exaggeration biases in online ratings, and the Results section finds that female drivers can receive a larger rating penalty than male drivers for a low-quality experience. These findings support questioning whether ratings accurately reflect performance, but the paper does not establish that customer satisfaction ratings are volatile or generally unreliable. (LLM, conf=0.84)
- Partly supportedcites Luca & Zervas, 2016 sourceExperimental — accuracy not yet measured
Section 2.2, “Fake and Filtered Reviews” (page unavailable), says fraudulent and selectively solicited Yelp reviews can produce a positively biased review sample, supporting concern about the reliability and validity of those ratings. The paper does not establish that customer satisfaction ratings generally are volatile, nor does it study ratings of workers. (LLM, conf=0.86)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“These authors claim that sociotechnical capital can only be optimized when AI technologies and employees act as a tightly coupled system exhibiting increased responsiveness.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Sociotechnical moderators
What the sources say
- Partly supportedcites Makarius et al., 2020 sourceExperimental — accuracy not yet measured
Section 3 says sociotechnical capital is likely to result when AI and employees are successfully integrated as a tightly coupled, responsive system. But it also says loosely coupled AI and employees can produce moderate sociotechnical capital. The source therefore does not support the claim that tight coupling is the only way to optimize it. (LLM, conf=0.87)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Consistent with this idea, one of the authors of the JD-R model stated that”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > HOW CAN ORGANIZATIONS ENSURE THAT AM ENABLES AND SUSTAINS WELL-DESIGN JOBS?
What the sources say
- Partly supportedcites Demerouti, 2020 sourceExperimental — accuracy not yet measured
The “(Negative) Consequences and How to Avoid Them” section (page not supplied) says digitalization and automation can contribute to stimulating, healthy jobs when people can control and craft their use and job resources are maximized while demands remain affordable. The claim omits two further conditions the paper includes: sharing economic growth with employees and protecting employees and employment conditions. (LLM, conf=0.83)
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Both needs and supply rely on algorithmic estimation, with the precise prediction of needs in workforce based on information such as expected or real-time customer traffic, deadlines, real-time monitoring of fluctuating demand, weather forecasts, or on previous occupancy at the same date (Cheng, Rao, Jiang, & Zhou, 2015;Hoshino, Slobodin, & Bernoudy, 2018).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic scheduling.
What the sources say
- Not checked — no full text of the sourcecites Cheng, Rao, Jiang, & Zhou, 2015 source
- Partly supportedcites Hoshino, Slobodin, & Bernoudy, 2018 sourceExperimental — accuracy not yet measured
The Mathematical Model (p. 3) uses employee availability and minimum and maximum staffing requirements as inputs to an algorithm that optimizes schedules. The Next Steps section (p. 6) says managers gather employee preferences and enter them into the program. The paper therefore supports algorithmic scheduling using information about needs and supply, but not the claim that the algorithm estimates both. (LLM, conf=0.79)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Some scholars have begun to apply STS theory to AI and the digitalization of work (Makarius et al., 2020;Parker & Grote, 2020;Shin & Park, 2019;Winby & Mohrman, 2018), stating that the fast pace of the recent technological progress has created an disequilibrium between the two components, such that technical systems and humans are often not jointly optimized.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Sociotechnical moderators
What the sources say
- Partly supportedcites Makarius et al., 2020 sourceExperimental — accuracy not yet measured
The Introduction (page unavailable) says STS theory focuses on jointly optimizing an organization’s human and technological dimensions. Section 2.2 (page unavailable) says few organizations have achieved their AI aspirations at scale. The paper does not establish that rapid technological progress has caused a general disequilibrium between social and technical systems, or that they are often not jointly optimized. (LLM, conf=0.84)
- Not matchedcites Parker & Grote, 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Shin & Park, 2019 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“One of the advocated solutions to this issue is to provide transparency in the data (i.e., data visibility), which could however conflict with the need to preserve the privacy of the data (Stohl et al., 2016;Zuboff, 2015).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
What the sources say
- Partly supportedcites Stohl et al., 2016Experimental — accuracy not yet measured
The Relationship Between Information Visibility and Transparency section links information visibility to transparency, and Legal obligation describes proprietary data being made public. But the passages do not discuss a conflict between data visibility and preserving data privacy; proprietary information is not necessarily private data in the sense claimed. (LLM, conf=0.84)
- Not checked — no full text of the sourcecites Zuboff, 2015 source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“transparency in the decisions of very complex machine learning algorithms with limited room for explainability is very difficult (and perhaps impossible) to achieve, and, if achieved, could be very demanding in terms of cognitive load for workers (Gal et al., 2020;Stohl, Stohl, & Leonardi, 2016).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
What the sources say
- Not checked — no full text of the sourcecites Gal et al., 2020 source
- Partly supportedcites Stohl, Stohl, & Leonardi, 2016Experimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Their findings indicate that, instead of hampering social support between nurses, the easiness to use the system to swap shifts in order to accommodate coworkers triggered a positive team climate and a reduction of interpersonal conflicts, increasing social support.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Human influence
What the sources say
- Partly supportedcites Uhde et al., 2020 sourceExperimental — accuracy not yet measured
In “Data souvereignity and transparency” (page not provided), the paper suggests that a scheduling system could facilitate pro-social behavior and may benefit team climate. It does not report that an easy-to-use system actually reduced interpersonal conflicts or increased social support. “Cultivate a positive team spirit” instead reports that existing respect and empathy increased willingness to swap shifts. (LLM, conf=0.88)
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“Job insecurity (+)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not checked — no full text of the sourcecites Van Oort (2019) source
- Could not verifycites Moore and Hayes (2017) sourceExperimental — accuracy not yet measured
The paper’s discussion of electronic monitoring and zero-hours contracts describes work-on-demand scheduling and uncertainty about paid time. Its ‘Electronic Monitoring – rationale and reality’ section describes a system that checks visits against a roster, but does not report an association between algorithmic scheduling and job insecurity. I searched for job insecurity, employment security, and scheduling in our copy; no passage establishes the claimed relationship. (LLM, conf=0.75)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Job insecurity (+)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not checked — no full text of the sourcecites Griesbach et al. (2019) source
- Not checked — no full text of the sourcecites Lehdonvirta (2018) source
- Partly supportedcites Wood et al. (2019) sourceExperimental — accuracy not yet measured
In Findings and discussion, the paper says algorithmic ratings and rankings can filter work away from lower-rated workers, and Worker power and competition reports that workers lacked formal job security and feared replacement. It does not identify algorithmic goal setting as a practice or report a positive association between goal setting and job insecurity. (LLM, conf=0.82)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The cited sources that could be checked couldn’t confirm or dispute this claim.
In the paper
“Autonomy (-)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not matchedcites Moore and Hayes (2017, 2018)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Griesbach et al. (2019) source
- Could not verifycites Wood et al. (2019) sourceExperimental — accuracy not yet measured
The Findings and discussion section describes algorithmic management as affording remote gig workers significant autonomy and discretion. A search for compensation, pay, and wages found discussion of earnings and platform ratings, but no assessment of whether algorithmic compensation is negatively associated with job autonomy. (LLM, conf=0.76)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Workload (+)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not checked — no full text of the sourcecites Levy (2015) source
- Supportedcites Bakewell et al. (2018) source
In “Flexibility, Accountability, and Intensification of Work” (page unavailable), the paper says the apps simplified some tasks but created space to intensify core work; engineers worked outside contracted hours and sometimes worked through breaks. This supports the claimed positive relationship with workload in the field-engineer setting, though the paper describes qualitative findings rather than a statistical association. (LLM, conf=0.86)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Most authors consider that only the advent of strong artificial intelligence (also called general AI), involving fully agentic and autonomous AI algorithms with potentially greater capabilities than human beings, could reasonably lead one to adopt a strict determinism perspective(Braga & Logan, 2017;Clifton, Glasmeier, & Gray, 2020).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Conclusion
What the sources say
- Partly supportedcites Braga & Logan, 2017 sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
- Not checked — no full text of the sourcecites Clifton, Glasmeier, & Gray, 2020 source
hedgeddirect- Asserted: fails — The authors may not put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The authors may not put it forward as true. The paper’s conclusions may not depend on it.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Job insecurity (+)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not checked — no full text of the sourcecites Veen et al. (2019) source
- Partly supportedcites Wood et al. (2019) sourceExperimental — accuracy not yet measured
In ‘Autonomy in the shadow of algorithmic management’ (page unavailable), the paper says algorithmic ratings can filter work away from lower-rated workers, making a living on the platform less viable. ‘Worker power and competition’ (page unavailable) reports job insecurity, but also attributes it to competition and the absence of formal job security. The paper does not report a measured positive association between algorithmic performance management and job insecurity. (LLM, conf=0.84)
- Partly supportedcites Evans and Kitchin (2018) sourceExperimental — accuracy not yet measured
The Introduction (page unavailable) links algorithm-governed work to precarious employment, which supports a general connection with insecurity. It does not establish a positive association specifically between algorithmic performance management and job insecurity; its discussion of performance monitoring addresses control of work rather than that outcome. (LLM, conf=0.78)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“In particular, AM has been associated with a reduction of workers' autonomy (Jabagi, Croteau, Audebrand, & Marsan, 2019;Mohlmann & Zalmanson, 2017;Toyoda, Lucas, & Gratch, 2020)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“These consequences potentially explain why AM has also been shown to result in in negative emotions, unfairness perceptions, low trust (Lee, 2018;Zarsky, 2016)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“These consequences potentially explain why AM has also been shown to result in in negative emotions, unfairness perceptions, low trust (Lee, 2018;Zarsky, 2016)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“These consequences potentially explain why AM has also been shown to result in in negative emotions, unfairness perceptions, low trust (Lee, 2018;Zarsky, 2016)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“and the creation of power asymmetry in information availability (Calo & Rosenblat, 2017;Jarrahi & Sutherland, 2018;Rosenblat & Stark, 2016;Shapiro, 2018).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
- Not matchedcites Calo & Rosenblat, 2017
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Jarrahi & Sutherland, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Rosenblat & Stark, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In our review, we similarly identified literature about algorithmic management both in the gig economy and in other sectors.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic management and its functions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“First, the emerging literature on the topic is spread across different streams of research and conceptual approaches, and has mainly examined one algorithmic function at the time, lacking theoretical integration.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“reduced engagement in work (Bucher, Fieseler, & Lutz, 2019)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
- Not checked — no full text of the sourcecites Bucher et al., 2019 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“psychological contract breach (Tomprou & Lee, 2019)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
- Not matchedcites Tomprou & Lee, 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Reyes (2018) namely reports how an algorithmic system used to dispatch room cleaning assignments based on instant clients' arrival time has taken away housekeepers' autonomy to organize their day and made their jobs more physically demanding”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic goal setting.
What the sources say
- Not matchedcites Reyes, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
In the paper
“lower life satisfaction (Keith, Harms, & Tay, 2019)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
- Not checked — no full text of the sourcecites Keith et al., 2019 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Such monitoring of numerous features of employees' attitudes, behaviors, performance, and emotions has largely been viewed as a pervasive form of surveillance, focused on controlling employees (Mateescu & Nguyen, 2019b), which can correspond to a stress-related emotional demand.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic monitoring.
What the sources say
- Not matchedcites Mateescu & Nguyen, 2019b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
- Not matched
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“low job satisfaction (Brawley & Pury, 2016;Griesbach, Reich, Elliott-Negri, & Milkman, 2019)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Second, existing research often seems to be based on deterministic assumptions about the consequences of technology, implying pre-determined outcomes.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In sum, research of the role and on the operationalization and interconnectedness of these constructs is nascent and warrants further development.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“while the impact on workers' autonomy is consistently negative across the six functions, the effect of each AM function on other job resources and demands is highly variable, suggesting the importance of considering functions separately.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > DISCUSSION AND CONCLUSION
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Algorithmic management has six actual functions that can be examined as distinct components.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“there is a lack of intervention research that actually examines whether making these sorts of changes to real systems in a proactive way indeed positively impacts work design and outcomes.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > DISCUSSION AND CONCLUSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“the evidence reviewed clearly highlights the influence of AM on work design characteristics, with most of this influence appearing to be negative.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > DISCUSSION AND CONCLUSION
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Algorithmic management has six actual functions that can be examined as distinct components.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“several further outcomes of work design could be included in the model, yet we have not done so as the evidence base currently does not exist.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“algorithmic performance management (PM) and scheduling seem to have more salient consequences on job demands than job resources, whereas for the other functions, there is more evidence of effects on job resources.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > DISCUSSION AND CONCLUSION
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Algorithmic management has six actual functions that can be examined as distinct components.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“To date, the evidence for the effect of these elements is limited, and our propositions are largely based on extrapolating from other fields of research (computing and data science, namely).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > DISCUSSION AND CONCLUSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“PM is also the function for which there is the most evidence for a bright side, with a potential improvement of role clarity and feedback from the job.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > DISCUSSION AND CONCLUSION
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Algorithmic management has six actual functions that can be examined as distinct components.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Such systems used, for instance, to monitor and optimize warehouse workers hands and arms movements (Engler, 2018;Yeginsu, 2018), or to track different features of parcel delivery process such as the geolocation, the cleanliness of the trucks (Woyke, 2018) and the weight and size of each package (Rosenbush, 2018) are likely to simplify workers jobs or solving problems for workers”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic monitoring.
What the sources say
- Not matchedcites Engler, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Yeginsu, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Woyke, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Existing research on algorithmic management tends to suggest that it generates more negative than positive outcomes for workers.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > INTRODUCTION
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“More specifically, as depicted in our model, we identified three critical and potentially inter-connected such parameters, which function as socio-technical moderators of the link between AM and its impact on work design: System transparency, system fairness, and human influence.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > 263).
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Similarly, algorithmic scheduling may facilitate the implementation of an organizational strategy towards zero-hours contract (Fleming, 2017;Moore & Hayes, 2017, 2018), resulting in lower job stability.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic scheduling.
What the sources say
- Not checked — no full text of the sourcecites Fleming, 2017 source
- Not matchedcites Moore & Hayes, 2017, 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“which could, rather yield confusion about the employer's or platform's expectations towards employees, reduce the quality of feedback and role clarity.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic performance management.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, the ability of algorithms to decide, implement, or facilitate job termination makes it easier for employers to proceed to job termination, which could potentially influence job insecurity perceptions.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic job termination.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
In the paper
“In orienting efforts towards activities that will be financially rewarded, performance-based compensation lowers the perception of autonomy and is more likely to generate a controlled and extrinsic type of motivation (Gagné & Forest, 2008).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic compensation.
What the sources say
- Not checked — no full text of the sourcecites Gagné & Forest, 2008 source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The companies' objectives in delegating scheduling to algorithms is generally to create on-demand and justin-time schedules quickly and automatically.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic scheduling.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Our moderate voluntaristic point of view leads us to postulate that the use of algorithmic management has consequences on workers, but that these effects can be influenced and managed by the decisions of stakeholders in organizations or institutions, as well as (to some extent) by the actions of individuals themselves.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > HOW CAN ORGANIZATIONS ENSURE THAT AM ENABLES AND SUSTAINS WELL-DESIGN JOBS?
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Literature also suggest that, like the call centers' emotional state monitoring described above and involving continuous requests of rapid emotional shifts, the greater use of customer monitoring and data in workers management require them to display exaggeratedly and sustained positive emotions in their online interactions with customers, increasing the risk of emotional demands (Van Oort, 2019).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic performance management.
What the sources say
- Not checked — no full text of the sourcecites Van Oort, 2019 source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Our research was guided by sociotechnical systems theory (STS : Cherns, 1976;Emery & Trist, 1978), which proposes that organizations perform better when their design jointly optimizes the social systems (i.e., the humans within and around the organization) and the technical system (i.e., technologies and mechanics supporting work processes) (Cherns, 1976;Emery & Trist, 1978).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Sociotechnical moderators
What the sources say
- Not checked — no full text of the sourcecites Cherns, 1976 source
- Not matchedcites Emery & Trist, 1978
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Furthermore, an emerging base for bonus or pay raise allocation is the algorithmic prediction of hypothetical future performance.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic compensation.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“In the same vein, Gregory (2020) showed that gig food deliverers feel obligated to follow the scheduling nudges displayed by the app and to sometimes work in adverse weather or very difficult conditions (physical demands), mainly because they don't know to what extent compliance to these incentives is reflected in performance scores or in future assignments.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > System Transparency
What the sources say
- Not matchedcites Gregory, 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
In the paper
“Another study observed that algorithmic compensation encourages the workers”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic compensation.
What the sources say
- Not checked — no full text of the sourcecites Galière, 2020 source
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The above discussion of AM functions and their consequences suggests that the outcomes for work design are principally negative, with AM tending to lower job resources and to increase job demands.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > HOW CAN ORGANIZATIONS ENSURE THAT AM ENABLES AND SUSTAINS WELL-DESIGN JOBS?
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The study by Newman et al. (2020) also showed that algorithm-based pay decisions made be perceived as reductionistic, and that such rewarding of quantified, unsignificant an decontextualized aspect might alter task significance.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic compensation.
What the sources say
- Not checked — no full text of the sourcecites Newman et al., 2020 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In terms of work design, algorithmic PM is, on the one hand, likely to augment the”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic performance management.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“First, algorithms can make the decision to terminate the employment of a worker and automatically notify the employee.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic job termination.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Because these metrics are generally easy to understand and straightforward (see Rosenblat & Stark, 2016, pp. 73-74 for examples of platform feedback notification), they also may increase the clarity of the expectations toward them, fostering role clarity.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic performance management.
What the sources say
- Not matchedcites Rosenblat & Stark, 2016
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Following this statement, and in accordance with the postulates of STS theory, the logic of our model is that algorithmic management could either enhance or hamper the achievement of quality work design, and hence impact individual outcomes and indeed firm productivity (or sociotechnical capital), depending on the interplay of technical characteristics and human workers.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > 263).
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“In terms of work design, algorithmic compensation might contribute to reduce the autonomy of the workers in constraining them to work longer hours and decrease the control they have on the rewards they gain from work (Goods, Veen, & Barratt, 2019;Griesbach et al., 2019;Moore & Hayes, 2017, 2018;Rani & Furrer, 2020;Wood et al., 2019).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Algorithmic compensation.
What the sources say
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Although the conceptualizations of algorithmic fairness differ among authors, its most common and accepted components are the absence (or minimization) of bias and discrimination (Choudhury, Starr, & Agarwal, 2020;Cowgill & Tucker, 2020;Jean, 2020;Lepri et al., 2018;Robert et al., 2020;Shin & Park, 2019;Wong, 2019), the accuracy and appropriateness of decisions (Shin, 2021;Shin & Park, 2019), the”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > System Fairness
What the sources say
- Not checked — no full text of the sourcecites Choudhury, Starr, & Agarwal, 2020 source
- Not matchedcites Cowgill & Tucker, 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Jean, 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the three proposed categories of moderators present significant practical challenges.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we recognise there is likely to be a moderating role of individual differences and of wider contextual elements such as organizational culture and labor market variables.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Also, keeping humans in the decision loop and preserving human voice is certainly important, but too much voice could impair at some point the benefits of automated decision-making and lead to a heavy and unfruitful decision-making process.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“there are potentially important moderating factors to do with the way that AM is designed and implemented that could mitigate AM's negative effects and enhance its positive effects.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > DISCUSSION AND CONCLUSION
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Physical demands (+)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not matchedcites Reyes (2018)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Gregory (2020)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“Social support (-)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not checked — no full text of the sourcecites Leclercq-Vandelannoitte (2017) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Job complexity (-)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not matchedcites Brione (2017, p. 12)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly, the extent to which schedules or goal-setting decisions are based on previous performance could shape the burdens associated with those decisions in terms of workload or physical demands.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > System Fairness
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Workload (+)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not checked — no full text of the sourcecites Lehdonvirta (2018) source
- Not matchedcites Levy and Barocas (2018)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“most experts concur that strong AI is either not likely to happen in the near future, or is unlikely to happen at all(Hagendorff & Wezel, 2019;Wang & Siau, 2019).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Conclusion
What the sources say
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The provision of fair algorithms, especially machine learning algorithms, is also a complex and challenging issue for computer scientists and managers (Jean, 2020;Lepri et al., 2018), and choices and decisions may depend on ethical orientations (Gal et al., 2020;Gibert, 2020;Martin, 2019a;Mittelstadt, Allo, Taddeo, Wachter, & Floridi, 2016).”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
What the sources say
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Feedback from the job (+/-)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not matchedcites Rosenblat and Stark (2016)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
None of the sources cited for this claim have been checked yet.
In the paper
“Task significance (-)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not matchedcites Moore (2016, 2017)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Newman et al. (2020) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
None of the sources cited for this claim have been checked yet.
In the paper
“Role clarity (+ / -)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not matchedcites Rosenblat and Stark (2016)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Bernstein and Li (2017) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The ability to contest prejudicial or erroneous algorithmic compensation or termination decisions might also help to protect workers' autonomy, as well as lower the probability of stressful job demands such as job insecurity.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Human influence
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In that sense, the reasonableness (level of intrusiveness, range of information collected) of the system is likely to attenuate the impact of monitoring on task variety and significance and to preserve the ability of workers to organize their tasks and methods.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > System Fairness
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“fostering transparency about the use and content of algorithmic systems may naturally contribute to lower biases, and allowing more human influence in the system is likely to trigger more relevant and legitimate automated decisions.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Limitations and future research
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We expect that this ability to opt out of the automated system or of its decision will increase job autonomy and maintain problemsolving opportunities.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > Human influence
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Task significance (-)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not checked — no full text of the sourcecites Newman et al. (2020) source
plaincorrelational- Asserted: fails — The authors may not put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The authors may not put it forward as true. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Bus drivers have access to a detailed and confidential breakdown of their areas of possible improvement, which seem to be perceived by drivers as feedback from the job and role clarity improvement.”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > System Fairness
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Workload (+)”
§ Algorithms as work designers: How algorithmic management influences the design of jobs > References
What the sources say
- Not matchedcites Liao (2018)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Burin (2019)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Yeginsu (2018)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper relies on this without support.
Algorithmic management has six actual functions that can be examined as distinct components.
“in unpacking the phenomenon of algorithmic management and its six (actual) functions, we develop a more holistic approach of algorithmic management, allowing its examination across the distinctly operating components rather than as a monolithic piece.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, managers and organizations might rob workers of this autonomy by closely monitoring them, for example by checking their computer or phone usage123.”
From Understanding and shaping the future of work with self-determination theory (2022) · cites this paper as [123]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Specifically, whether algorithmic management systems consider human motivational factors in their design influences whether workers are given enough autonomy, skills usage, task variety, social contact, role clarity (including knowing the impact of one’s work) and a manageable workload123.”
From Understanding and shaping the future of work with self-determination theory (2022) · cites this paper as [123]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“In addition, algorithmic management is often associated with simplified tasks, and with lower problem-solving opportunities and job variety123.”
From Understanding and shaping the future of work with self-determination theory (2022) · cites this paper as [123]
The cited source says what the claim attributes to it.
In the citing paper
“Because these types of quantified metric are often directly linked to performance scores, pay incentives and future allocation of tasks or schedules (that is, getting future work), algorithmic management reduces workers’ freedom in decision-making related to their work, which can significantly reduce their self-determined motivation123.”
From Understanding and shaping the future of work with self-determination theory (2022) · cites this paper as [123]
Citations
Cites
The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior
Deci, E. L., & Ryan, R. M. (2000) · Psychological Inquiry · doi:10.1207/s15327965pli1104_01 · Cited by 34,210
The job demands-resources model of burnout.
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001) · Journal of Applied Psychology · doi:10.1037/0021-9010.86.3.499 · Cited by 13,643
The Job Demands‐Resources model: state of the art
Bakker, A. B., & Demerouti, E. (2007) · Journal of Managerial Psychology · doi:10.1108/02683940710733115 · Cited by 12,996
Motivation through the design of work: test of a theory
Hackman, J. R., & Oldham, G. R. (1976) · Organizational Behavior and Human Performance · doi:10.1016/0030-5073(76)90016-7 · Cited by 8,962
Explanation in artificial intelligence: Insights from the social sciences
Miller, T. (2019) · Artificial Intelligence · doi:10.1016/j.artint.2018.07.007 · Cited by 5,302
The Duality of Technology: Rethinking the Concept of Technology in Organizations
Orlikowski, W. J. (1992) · Organization Science · doi:10.1287/orsc.3.3.398 · Cited by 4,957
The ethics of algorithms: Mapping the debate
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016) · Big Data & Society · doi:10.1177/2053951716679679 · Cited by 4,567
Big other: Surveillance Capitalism and the Prospects of an Information Civilization
Zuboff, S. (2015) · Journal of Information Technology · doi:10.1057/jit.2015.5 · Cited by 3,205
Morgeson, F. P., & Humphrey, S. E. (2006) · Journal of Applied Psychology · doi:10.1037/0021-9010.91.6.1321 · Cited by 2,994
Human trust in artificial intelligence: Review of empirical research
Glikson, E., & Woolley, A. W. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0057 · Cited by 2,921
Research works printed but not linked: 15
- De La Garza, 2019, This AI software is “Coaching” customer service workers. Soon It Could Be Bossing You Around, Too, Times, 7/8/2019
- Eveleth, 2019, Your employer may be spying on you—And wasting its time, Scientific American, 321
- Gershgorn, 2015, Hitachi hires artificially intelligent bosses for their warehouses, Popular Science
- Gibert, 2020, Vol. 17
- Hernandez, 2018, How computers could make your customer-service calls more human, The Wall Street Journal (online)
- Hodson, 2014, The AI boss that deploys Hong Kong's subway engineers, New Scientist
- Levy, 2018, Refractive surveillance: Monitoring customers to manage workers, International Journal of Communication, 12, 1166
- O'Connor, 2016, When your boss is an algorithm, Financial Times.
- O'Donovan, 2018, An Invisible Rating System At Your Favorite Chain Restaurant Is Costing Your Server, BuzzFeed News
- Rosenbush, 2018, The Morning download: UPS expands role of predictive analytics, The Wall Street Journal.
- de Ruyter, 2019, Gig work and the Foruth industrial revolution, Journal of International Affairs, 72, 37
- Stevens, 2015, At UPS, the algorithm is the driver, The Wall Street Journal
- Waterson, 2016, Daily telegraph installs workplace monitors on journalists' desks, BuzzFeed News
- Williams, 2017, How the gap used an app to give workers more control over their schedules, Harvard Business Review
- Yeginsu, 2018, If workers slack off, the wristband will know. (and Amazon has a patent for it.), The New York Times
Cited by
Sorted by citations
Items 501–508 of 508
Koppalkar, S. R. (2026) · doi:10.64823/ijstm.2601005
“Algorithmic control is extensive; agents extend it to action [5]–[7], [11], [20], [30]–[32] The question is no longer whether software manages work, but which actions it may take alone F2.”
Rabethge, N., Bentler, D., Kümmert, F., & Maier, G. W. (2026) · Intelligente Technische Systeme, Lösungen aus dem Spitzencluster it’s OWL · doi:10.1007/978-3-662-73053-9_4
Intelligente Personaleinsatzplanung in der Produktion
Gabriel, S., Bentler, D., Bansmann, M., Latos, B. A., Maier, G., & Dumitrescu, R. (2026) · Intelligente Technische Systeme, Lösungen aus dem Spitzencluster it’s OWL · doi:10.1007/978-3-662-73053-9_12
Kauttonen, J., Tuomi, A., Vuori, J., Saaranen, P., & Lahtinen, A. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2750593
Liang, S., Jiang, J., & Chen, J. (2026) · Scientific Reports · doi:10.1038/s41598-026-63763-x
“As a subjective cognitive set of individuals toward AI-induced career replacement risks, AI awareness is associated with university students perceiving potential threats to core career resources such as skill depreciation, job security, and career development paths 62,5 .”
Influentialİnsan Kaynakları Yönetimi ve Sosyal Politika: Emek, Güç ve Kurumsal Sınırlar
Koçancı, M. (2026) · Özgür Yayınları eBooks · doi:10.58830/ozgur.pub1562
Perceived algorithmic control and courier safety risk in last-mile delivery: a transparency paradox
Lin, Y., Zhao, Q., & Chang, J. (2026) · Industrial Management & Data Systems · doi:10.1108/imds-03-2026-0356
Dijital Taylorizm literatürünün bilimsel gelişimi: Bibliyometrik bir analiz
Köksal, Ö., & Akdemir, M. A. (2026) · Akademik Açı · doi:10.59597/akademikaci.1979525
Metadata
- Authors
- Parent-Rocheleau, X., & Parker, S. K.
- Affiliations
- Curtin University (AU)
- ORCID
- Parker, Sharon K.
- Venue
- Human Resource Management Review
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 32
- Issue
- 3
- Pages
- 100838
- ISSN
- 1053-4822 (ISSN-L)
- OpenAlex
- W3161181201
- Semantic Scholar
- 7f867c7f4b67961c21507e959d13ecd5af949179
- Cited by
- 512
- References
- 185
- Citations by year
- 2026: 199 · 2025: 137 · 2024: 93 · 2023: 43 · 2022: 37
- FWCI
- 60.93
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 1011 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Human Resource Management Review (acceptedVersion)
- eSpace (Curtin University) (submittedVersion, cc-by-nc-nd)
- Funders
- Social Sciences and Humanities Research Council of Canada (756-2019-0094)
- Australian Research Council (FL160100033)
- Topics
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
- Keywords
- algorithmic management, job design, employee autonomy, job complexity, workload, performance management, goal setting, job scheduling, compensation, dismissal, employee motivation, employee well-being, transparency, fairness, human influence, socio-technical systems theory, meaningful work
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-30, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-30 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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