Bibliographic record
Abstract
Satisficing theories, whether of rationality or morality, do not require agents to maximize the good. They demand only that agents bring about outcomes that are, in one or both of two senses, "good enough." In the first sense, an outcome is good enough if it is above some absolute threshold of goodness; this yields a view that I will call absolute-level satisficing. In the second sense, an outcome is good enough if it is reasonably close to the best outcome the agent could bring about; this leads to what I will call comparative satisficing. These two views coincide in their implications for a specific sort of case, in which the situation is now fairly far below the absolute-level threshold and an agent can at best bring it to a point somewhat above that threshold. Here both absolute-level and comparative satisficing say that one need not bring about the best available outcome, though of course one may; one is required only to improve the situation to the absolute threshold. But in other cases the views diverge. If the situation is now far below the absolute threshold and, no matter what, will remain below it, absolute-level satisficing requires agents to do everything they can to improve the situation; here its implications coincide with those of maximizing. But comparative satisficing is less demanding, requiring agents only to make some reasonable percentage of the largest improvement they can.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".