What Do Public Sociologists Do? A Critique of Burawoy
Bibliographic record
Abstract
Michael Burawoy certainly seems to have the requisite organizational and marketing savvy to be a successful ‘public sociologist.’ Preaching from a few well-chosen pulpits, the ASA Presidency first among them, he has almost singlehandedly created a multinational cottage industry busily debating his ideas about the future of our discipline. The responses have been as varied as they have been numerous. While many have been quite critical, the criticisms have originated from a bewildering range of often entirely opposite positions on the ideological-philosophical spectrum, as well as from every imaginable position in between. Burawoy himself takes this multiplicity of position-takings to be evidence for the plausibility of his own ideas about different kinds of sociology and the possibility of a fruitful, collaborative division of labour between them (Burawoy 2007: 246). But we suspect it is more likely simply an expression of the depth and the breadth of our discord concerning the basic question of what we want with our discipline .
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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 | 0.030 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.086 |
| Scholarly communication | 0.023 | 0.030 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.024 | 0.026 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".