Bibliographic record
Abstract
Friendship and romantic love are, by their very nature, exclusive relationships. This paper suggests that we can better understand the nature of the exclusivity in question by understanding what is wrong with the view of practical reasoning I call the Comprehensive Surveyor View. The CSV claims that practical reasoning, in order to be rational, must be a process of choosing the best available alternative from a perspective that is as detached and objective as possible. But this view, while it means to be neutral between various value-bearers, in fact incorporates a bias against those value-bearers that can only be appreciated from a perspective that is not detached—that can only be appreciated, for instance, by agents who bear long-term commitments to the values in question. In the realm of personal relationships, such commitments tend to give rise to the sort of exclusivity that characterizes friendship and romantic love; they prevent the agent from being impartial between her beloved’s needs, interests, etc., and those of other persons. In such contexts, I suggest, needs and claims of other persons may be silenced in much the way that, as John McDowell has suggested, the temptations of immorality are silenced for the virtuous agent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.068 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".