Private regulation, public policy, and the perils of adverse ontological selection
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
Abstract What problems can private regulatory governance solve, and what role should public policy play? Despite access to the same empirical evidence, the current scholarship on private governance offers widely divergent answers to these questions. Through a critical review, this paper details five ontologically distinct academic logics – calculated strategic behavior; learning and experimentalist processes; political institutionalism; global value chain and convention theory; and neo‐Gramscian accounts – that offer divergent conclusions based on the particular facets of private governance they illuminate, while ignoring those they obfuscate. In this crowded marketplace of ideas, scholars and practitioners are in danger of adverse ontological selection whereby certain approaches and insights are systematically ignored and certain problem conceptions are prioritized over others. As a corrective, we encourage scholars to make their assumptions explicit, and occasionally switch between logics, to better understand private governance's problem‐solving potential and its interactions with public policy.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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