Bibliographic record
Abstract
Finding Values Public Sector Ethics: Prospects and Challenges Tom Sherman Against Professional Ethics Hendrik THG Kaptein Authority, Discretion and Accountability: The Case of Policing Seumas Miller Business Practices and the Public Service Ethos Alan Lawton Clarifying Accountability: An Ethical Theory Framework Mel Dubnick Implementing Values Ethics in Public Service: An Idea Whose Time Has Come Stephen D Potts Corruption in Socialist and Capitalist Countries Young Jong Kim Integrating Ethics Colin Hicks and Gerald Scanlan Canadian Defence Ethics: Principles and Values Rosalie Bernier Administrative Law and Good Government Roger Douglas Public Sector Managers, Public Sector Workers and Ethics: A Trade Union Perspective Adrienne Taylor and Mike Waghorne Talkin' 'Bout Hebn David Corbett References/ Index
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".