Theory and Contrastive Explanation in Ethnography
Abstract
We propose three interlinked ways that theory helps researchers build causal claims from ethnographic research. First, theory guides the casing and re-casing of a topic of study. Second, theoretical work helps craft a clear causal question via the construction of a contrast space of the topic of investigation. Third, the researcher uses theory to identify social mechanisms that condense causal accounts. We show how each step can accommodate the everyday meanings typically central to ethnographic research’s contributions. This tripartite role for theory thus preserves ethnography’s traditionally recognized strength in interpretive validity, while realizing ethnography’s potential for offering causal, and partly generalizable, accounts that can engage the wider sociological discipline. The discussion brings ethnographic research into conversation with recent debates on the role of mechanisms, comparative and counterfactual thinking in causal accounts. We illustrate and defend our argument for theory in ethnography with an extensive analysis of a contemporary ethnographic monograph along with briefer attention to parallel uses of theory in two other ethnographic studies.
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In three studies [67], [128], [137], the classifiers used in the experiments are not specified.
“In three studies [67], [128], [137], the classifiers used in the experiments are not specified.”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [128]
Akula et al. [128] present an empirical study where input video frames are paired with the corresponding AND-OR graphs, i.e., compositional recursively defined graph-based knowledge representations capturing contextual information.
“For instance, Akula et al. [128] present an empirical study where input video frames are paired with the corresponding AND-OR graphs, i.e., compositional recursively defined graphbased knowledge representations capturing contextual information.”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [128]
In Akula et al.'s study [128], the explanations based on such graphs are passed on to human subjects to evaluate the contrastive answers to the predefined questions.
“The explanations based on such graphs are passed on to human subjects to evaluate the contrastive answers to the predefined questions.”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [128]
Single-sentence textual counterfactual explanations answer end-user's inquiries with respect to the automatic decision in question.
“They also answer end-user's inquiries with respect to the automatic decision in question [128], [159].”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [128]
The two aforementioned studies [128], [137] lack an evaluation of the quality of the generated counterfactual explanations themselves.
“However, the two aforementioned studies [128], [137] lack an evaluation of the quality of the generated contfactual explanations themselves.”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [128]
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- Authors
- Lichterman, P., & Reed, I. A.
- Affiliations
- University of Southern California (US)
- University of Colorado Boulder (US)
- Corresponding author
- Lichterman, Paul
- ORCID
- Reed, Isaac Ariail
- Venue
- Sociological Methods & Research
- Publisher
- SAGE Publications
- Published
- 2014-10-27
- Volume
- 44
- Issue
- 4
- Pages
- 585-635
- ISSN
- 0049-1241 (ISSN-L)
- 1552-8294
- OpenAlex
- W2131057858
- Semantic Scholar
- a4bd88abffaf012dedf2316fe0e2a489d0ed5ec9
- Cited by
- 71
- References
- 100
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 5 · 2023: 23 · 2022: 7 · 2021: 3 · 2020: 7 · 2019: 9 · 2017: 1 · 2016: 2 · 2015: 4
- FWCI
- 7.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Sociological Methods & Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Qualitative Comparative Analysis Research
- Social Sciences › Education › Qualitative Research Methods and Applications
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- causal explanation, contrastive explanations, social mechanisms, causal claims, counterfactual reasoning, comparative reasoning, interpretive validity, generalizability
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