Bibliographic record
Abstract
This article argues that we must distinguish between two distinct currents in the politics of recognition, one centred on demands for equal respect which is consistent with liberal egalitarianism, and one which centres on demands for esteem made on behalf of particular groups which is at odds with egalitarian aims. A variety of claims associated with the politics of recognition are assessed and it is argued that these are readily accommodated within contemporary liberal egalitarian theory. It is argued that, pace Taylor, much of what passes for `identity' or recognition politics is driven by demands for equal respect, not by demands for esteem/affirmation. Given the inherently hierarchical nature of esteem recognition, no liberal state can consistently grant such recognition. Furthermore, these demands pose the risk of intensifying intergroup competition and chauvinism. Esteem recognition is valuable for individuals, but plays a problematic role for egalitarian politics.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".