Bibliographic record
Abstract
T. M. Scanlon has cited the value of friendship in arguing against a ‘teleological’ view of value which says that value inheres only in states of affairs and demands only that we promote it. This article argues that, whatever the teleological view's final merits, the case against it cannot be made on the basis of friendship. The view can capture Scanlon's claims about friendship if it holds, as it can consistently with its basic ideas, that (i) friendship is a higher-level good consisting in appropriate attitudes to other goods and evils in a friend's life, (ii) these goods and evils have agent-relative value, i.e. more value than similar states of strangers, and (iii) the attitudes constituting friendship have less value than their objects. Given these independently plausible claims, the teleological view can agree with Scanlon that, e.g., it is wrong to betray a friend in order to promote more friendships among other people.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.025 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".