Time to certify: Explaining varying efficiency of private regulatory audits
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 Private regulatory programs, such as certification schemes, seek to control market access by providing greater certainty about products' credence attributes, including sustainability features of production processes. This article contributes to the literature that assesses the verification processes that determine whether private rules are being followed sufficiently by applicant rule‐targets (usually companies), and the regulatory intermediaries (auditors, assessors) that perform verification functions. By examining variation in the duration of verification processes of applicant rule‐targets, we question the assumption that within the context of a given program's design the efficiency of the verification process is invariant across time and space. We argue that the verification process can impose hurdles that are independent of rule‐targets' sustainability and their adherence to a private program's rules. Our analysis of 312 fisheries seeking Marine Stewardship Council certification shows that variation among intermediaries and objections to their certification decisions explain differences in the time it takes fisheries to receive market access.
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