Opportunity Costs and Resource Allocation Problems: Epistemology for Finite Minds
Bibliographic record
Abstract
Abstract Overwhelmingly, philosophers tend to work on the assumption that epistemic justification is a normative status that supervenes on the relation between a cognitive subject, some body of evidence, and a particular proposition (or “hypothesis”). This article will explore some motivations for moving in the direction of a rather different view. On this view, we are invited to think of the relevant epistemic norm(s) as applying more widely to the competent exercise of epistemic agency, where it is understood that cognitive subjects are simultaneously engaged in a number of different epistemic pursuits (distinct “lines of inquiry”), each placing irreconcilable demands on our limited cognitive resources. In effect, adopting this view would require shifting our normative epistemic concern away from the question of how a subject stands with respect to the evidence bearing on the hypothesis at stake in any one line of inquiry, and over onto the question of how well they cope with the inherent risks of epistemic resource management across several lines of inquiry. While this conclusion brings to light important connections between practical and epistemic rationality, it does not collapse the distinction between them. It does, however, constitute a step in the direction of a more systematically developed account of “non-ideal epistemology.”
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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 | 0.001 | 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 | 0.000 |
| 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".