'Alas poor Hicks', indeed! Sixty years of use and abuse: commentary on Bromwich et al
Bibliographic record
Abstract
Alas indeed! We might well wonder whether Professor Ray Chambers would have had the same reservations about using ‘Alas poor Hicks’ to describe what he perceived to be the ‘carelessness and indifference . . . [of] . . . so many . . . who clutched [so] indiscriminately at [Hicks' notion of income]’ had he experienced the matters which Bromwich et al. explain in their ‘Hicksian Income . . .’ in this issue. In a recently discovered 1976 letter to Sir John Hicks (reproduced as an appendix to this comment—and to which there is no evidence in the Chambers Archive of any reply by Hicks) Ray Chambers commented on accountants' cavalier treatment of Hicks on Income, treatment similar to that by the IASB and FASB of which Bromwich et al. now rightly complain.
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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 | 0.019 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.057 | 0.069 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".