Cost-benefit analysis, ethical values, and a ‘taste’ for fairness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A challenge for cost-benefit analysis is that it ignores ethical values such as justice, fairness, and equity. One standard response is to regard CBA results as just one factor in a more complex decision-process where ethical and democratic factors are also considered. This paper considers an alternative response: extending CBA so that it takes into account not only self-interested input but also moral preferences such as a ‘taste’ for fairness. Drawing on existing research and the example of resource allocation, the paper develops and analyzes objections to extended CBA. Evaluation of these objections, the paper shows, depends on how the original challenge is interpreted and how the problem of ‘ignoring’ ethical values is understood. While some interpretations lead to an impasse between defenders and critics of extended CBA, the paper proposes a novel interpretation – focused on political representationality – and showcases the limits of CBA as a coherent response.
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.
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 | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it