Governing through Standards: Networks, Failure and Auditing
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
This article seeks to understand network governance within the context of the North American automotive industry. Within this industry, original equipment manufacturers (lead firms) have outsourced a substantial portion of parts production over the last 30 years. This paper argues that in an aim to govern their supplier relations, North American lead firms imposed quality assurance standards upon their suppliers. In addition, this paper considers how nodes situated in the network are called upon to pre-emptively manage failures. Utilizing the quality assurance standards themselves, and 15 in-depth interviews with quality assurance managers at different part supplier plants, this article explores the technologies of performance used to manage failures. The focus of this paper is on the creation of part narratives, and particularly, the quality audit and its role in governing the conduct of part suppliers at-a-distance. Lastly, this paper focuses on the network prudential subject who is called upon to pre-emptively manage failures on behalf of the network.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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