Bibliographic record
Abstract
G.A. Cohen argues that Rawlsian constructivism mistakenly conflates principles of justice with optimal rules of regulation, a confusion that arises out of how Rawls has us think about justice. I use the concepts/conceptions distinction to argue that while citizens may reasonably disagree about the substance and demands of justice, some principled convergence may be possible: we can agree upon regulative principles consistent with justice, as each of us understands it. Rawlian constructivism helps us find that principled convergence, and this too is a conception of justice. G.A. Cohen pense que le constructivisme confond les principes de justice avec les règles de régulation optimale, une confusion qui découle de la manière dont Rawls pense la justice. En utilisant la distinction entre les concepts et les conceptions, j'affirme que, bien que les citoyens puissent raisonnablement contester la substance et les exigences de la justice, un accord de principe est possible: nous pouvons convenir de principes régulateurs compatibles avec la justice, comme chacun de nous la comprend. Le constructivisme Rawlsien nous aide à trouver cet accord de principe, et cela aussi est une conception de la justice.
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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 | 0.012 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.075 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.010 |
| 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".