Analysing, Accounting for and Unmasking Domination: On Our Role as Scholars of Practice, Practitioners of Social Science and Public Intellectuals
Bibliographic record
Abstract
Over the last 30 years, there has been an increasing interest in organizational analysis for the work of Pierre Bourdieu. However, the consequent body of literature often lacks an integrated comprehension of Bourdieusian theory and therefore fails to fully exploit its potentialities. In this essay, we argue for a more systematic engagement with the work of Bourdieu by organizational scholars and emphasize the opportunity to develop cumulative research on domination within and between organizations. The means by which systems of domination are reproduced without conscious intention by agents is a central issue for Bourdieu and arguably the primary reason for the development of his theoretical framework. It is thus through the study of domination that one can acquire a panoramic vision of Bourdieusian concepts that have been otherwise too often tackled separately. Moreover, domination is also a key entry to the understanding of how social scientists produce their own knowledge and of their role as members of society. We emphasize that as scholars, we have a moral responsibility to be reflexive about our practice and the social worlds we study in order to ultimately use the knowledge we produce to inform and direct social progress.
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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 | 0.112 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.013 | 0.135 |
| Scholarly communication | 0.029 | 0.052 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".