Institutional Ecology, `Translations' and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39
Abstract
Scientific work is heterogeneous, requiring many different actors and viewpoints. It also requires cooperation. The two create tension between divergent viewpoints and the need for generalizable findings. We present a model of how one group of actors managed this tension. It draws on the work of amateurs, professionals, administrators and others connected to the Museum of Vertebrate Zoology at the University of California, Berkeley, during its early years. Extending the Latour-Callon model of interessement, two major activities are central for translating between viewpoints: standardization of methods, and the development of `boundary objects'. Boundary objects are both adaptable to different viewpoints and robust enough to maintain identity across them. We distinguish four types of boundary objects: repositories, ideal types, coincident boundaries and standardized forms.
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The interpretive flexibility of the Bayesian framework functions as a boundary object in science studies terms.
“This interpretive flexibility functions as a form of “boundary object” in science studies terms—a conceptual entity that is plastic enough to adapt to local needs while robust enough to maintain a common identity across contexts (Star and Griesemer 1989).”
From The myth of the Bayesian brain (2025) · cites this paper as Star and Griesemer 1989
Legitimate authority depends upon institutional recognition rather than technical capability alone.
“Legitimate authority depends upon institutional recognition rather than technical capability alone [37].”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [37]
Authority is not about who possesses the greatest capacity to influence others, but about whose judgments are accepted as rightful and why.
“The central issue is therefore not who possesses the greatest capacity to influence others, but whose judgments are accepted as rightful and why [37].”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [37]
Authority should not be conflated with power.
“Authority should not be conflated with power [37].”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [37]
Digital platforms, algorithmic systems, and generative AI increasingly participate in the production and circulation of religious knowledge.
“Digital platforms, algorithmic systems, and generative AI increasingly participate in the production and circulation of religious knowledge”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [37]
Interpretive legitimacy continues to depend upon institutional authorization, representative mediation, communal recognition, and accountable governance.
“yet interpretive legitimacy continues to depend upon institutional authorization, representative mediation, communal recognition, and accountable governance [13,18,32,37].”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [37]
The checklist functions as a boundary object, enabling coordination between technical reviewers, domain scholars, and institutional gatekeepers without requiring epistemic consensus.
“The checklist functions as a boundary object [37], enabling coordination between technical reviewers, domain scholars, and institutional gatekeepers without requiring epistemic consensus.”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [37]
Prompt templates, segmentation rules, and annotation schemas are reported as part of the study's procedural record, enabling reviewers and institutional gatekeepers to trace how analytic claims move from text to output and where interpretive discretion is exercised.
“Prompt templates, segmentation rules, and annotation schemas are reported as part of the study's procedural record, enabling reviewers and institutional gatekeepers to trace how analytic claims move from text to output and where interpretive discretion is exercised [20,37].”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [37]
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- Authors
- Star, S. L., & Griesemer, J. R.
- Affiliations
- University of California, Irvine (US)
- University of California, Davis (US)
- ORCID
- Griesemer, James R.
- Venue
- Social Studies of Science
- Publisher
- SAGE Publications
- Published
- 1989-08
- Volume
- 19
- Issue
- 3
- Pages
- 387-420
- ISSN
- 0036-8539 (ISSN-L)
- 0306-3127
- 1460-3659
- OpenAlex
- W1971670344
- Cited by
- 10,847
- References
- 23
- Citations by year
- 2026: 733 · 2025: 625 · 2024: 536 · 2023: 566 · 2022: 620 · 2021: 605 · 2020: 605 · 2019: 581 · 2018: 501 · 2017: 515 · 2016: 512 · 2015: 484 · 2014: 504 · 2013: 437 · 2012: 525
- FWCI
- 47.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Social Studies of Science (publishedVersion)
- Topics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › History of Science and Natural History
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Diverse Historical and Scientific Studies
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Historical Studies and Socio-cultural Analysis
- Keywords
- institutional ecology, boundary objects, Museum of Vertebrate Zoology, University of California, Berkeley, method standardization, ideal types, repositories, standardized forms
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.
Statistics and arithmetic are recomputed, not judged.
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