Bibliographic record
Abstract
The work of early pluralist thinkers, from Arthur Bentley to Robert Dahl, inspired much optimism about democracy. They argued that democracy was functioning well, despite disagreements arising among the diversity of interests represented in policy-making processes. Yet it is unlikely that anyone paying attention to news coverage today would share such optimism. The media portray current policy-making processes as intractably polarized, devoid of any opportunity to move forward and adopt essential policy changes. This book aims to revive our long-lost sense of optimism about policy-making and democracy. Through original research into biotechnology policy-making in North America and Europe, Éric Montpetit shows that the depiction of policy-making offered by early pluralist thinkers is not so far off the present reality. Today's policy decision-making process - complete with disagreement among the participants - is consistent with what might be expected in a pluralist society, in sharp contrast with the negative image projected by the media.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.040 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".