Bibliographic record
Abstract
Many social scientists have argued that research should be designed to perform a ‘critical’ function, in the sense of challenging the socio-political status quo. However, very often, the relationship between the political value judgements underpinning this commitment and the values intrinsic to inquiry, as a distinct form of activity has been left obscure. Furthermore, the validity of those judgements has usually been treated either as obvious or as a matter of personal commitment. But there is an influential tradition of work that claims to derive evaluative and prescriptive conclusions about current society directly from factual investigation of its history and character. In the nineteenth century, Hegel and Marx were distinctive in treating the force of ethical and political ideals as stemming from the process of social development itself, rather than as coming from a separate realm, in the manner of Kant. Of course, the weaknesses of teleological meta-narratives of this kind soon came to be widely recognised, and ‘critical’ researchers rarely appeal to them explicitly today. It is therefore of some significance that, under the banner of critical realism, Bhaskar and others have put forward arguments that are designed to serve a similar function, while avoiding the problems associated with teleological justification. The claim is that it is possible to derive negative evaluations of actions and institutions, along with prescriptions for change, solely from the premise that these promote false ideas, or that they frustrate the meeting of needs. In this article I assess these arguments, but conclude that they fail to provide effective support for a ‘critical’ sociology.
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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 | 0.150 | 0.218 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.009 | 0.118 |
| Scholarly communication | 0.019 | 0.035 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.025 | 0.034 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".