Frames of Justice: Implications for Social Policy, Leroy H. Pelton, New Brunswick, New Jersey, USA, Transaction Publishers, 2005, pp. xi + 222, ISBN 0765802961, $49.95
Bibliographic record
Abstract
This book falls into that category of idiosyncratic, thought-provoking work, which, for one reason or another, occupies a marginal rather than a central place on the bookshelf. It is an original book, but the fate of originality is that it doesn't inevitably find universal favour. The reason in this case is certainly not to do with the quality of the scholarship or argument and may have more to do with the fact that, as Hamlet observed (Act 1, scene V), the time is out of joint—he isn't convinced he is the man to set things right. I think Pelton is aware of this and there are clues to his doubts, almost defensiveness from time to time. For instance, of the first chapter, based heavily on an analysis of Biblical texts, he says ‘The conclusions I draw within the first chapter are certainly open to challenge. But I have presented my case, and the burden shifts to those who would dispute my claims … ’ (p. xi). I don't think he should be defensive. The arguments he makes are no less powerful because they are illustrated with his chosen texts, even if they aren't all my first choice.
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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.020 | 0.026 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.069 | 0.013 |
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".