The Complexities of the Automotive Industry: positive and negative feedbacks in production systems
Why this work is in the frame
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Bibliographic record
Abstract
Abstract (English): 
 
 This paper utilizes complexity theory to analyze the implications of systemic changes that have occurred over the last 30 years in the automotive industry. We argue by dint of complexity analysis that the networked automotive production system characterized by just in time and lean production creates states far from equilibrium in individual parts manufacturers and assembler plants. Positive feedback creates system disturbances and adverse health and safety issues in the local plant environments. In addition, we examine four mechanisms that serve as negative feedback loops to absorb stresses in local plant environments and rectify health and safety related issues. This paper draws on thirty interviews with health and safety representatives at automotive manufacturing and assembly plants.
 
 Abstract (French):
 
 Ce papier utilise la théorie de complexité pour analyser les implications de changements systémiques qui se sont produits pendant les trente dernières années dans l'industrie automotrice. Nous soutenons, au moyen de l'analyse de complexité, que le système de production automoteur en réseau, caractérisé par la production juste à temps et mince, crée des états loin de l'équilibre dans les fabricants de parties individuels et les usines d'assembleur. Les rétroactions positives créent des dérangements dans le système qui causent des conditions défavorables de santé et sécurité dans les environs locaux de l’usine. En plus, nous examinons quatre mécanismes qui servent comme boucles de rétroactions négatives pour absorber ces tensions environnementales, et résoudre les problèmes de santé et sécurité. Ce papier est comprit de trente entretiens avec des représentants de santé et sécurité venant des usines fabricants et d’assemblage automotrices.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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