On Interdisciplinary Movements: The Development of a Network of Support Around Foucaultian Perspectives in Accounting Research
Bibliographic record
Abstract
This paper seeks to better understand interdisciplinary movements in the making. Our investigation focuses on the processes through which a network of support surrounding Michel Foucault's ideas originally developed in the sociological and organizational stream of accounting research. Drawing on the sociology of translation, we first examine how a network of support emerged around the journal Accounting, Organizations and Society (AOS), which is generally perceived as the main vector of dissemination of sociological and organizational accounting research. Our investigation then focuses on how Foucault's ideas, a few years after the founding of AOS, came to the attention of a group of accounting academics in the United Kingdom - a group in which the editor-in-chief of AOS was a key actor. We also examine how a network of support surrounding Foucault's ideas subsequently developed in the greater accounting research community. Our analysis emphasizes the role of epistemological uncertainty in the constitution of networks of support around journals and ideas, and the role of trials of strength (Latour, 1987) in fuelling or mitigating this uncertainty, thereby influencing actors' interests and commitments to particular networks. Our analysis also highlights the critical role that imitation and social differentiation play in the travel of ideas between scientific fields and the creation of scientific knowledge.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.015 | 0.061 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".