High Involvement Work Systems and Job Insecurity in the International Iron and Steel Industry
Bibliographic record
Abstract
Abstract The different factors behind globalization and the emergence of high involvement work practices do not necessarily carry similar implications for labour. The purpose of this paper is to examine the effects of high involvement work systems upon workers in the steel industry. The authors present results from a series of cross‐national sun>eys conducted in 1998 with 39 national trade unions from over 30 countries measuring issues such as job security, ownership changes, numerical flexibility, and union density. The findings are consistent with U.S. data reported by Osterman (1998) indicating that new work practices provide no defense against an environment of heightened Insecurity. Résumé Les différents facteurs qui encouragent la mondialisa‐tion et le dévoloppement de nouvelles pratiques de travail, dites “high involvement” (travail en équipes, rotation des fonctions, plus grande autonomie des employés) n'entraînent pas nécessairement des consequences semblables pour la main d'oeuvre. Nous examinons dans cette étude les effets de ces pratiques “high involvement” sur les travailleurs métallurgiques. Les auteurs publient les résultas de sondages interna‐tionaux effectués en 1998 auprès de 39 syndicats dans plus de 30 pays, permettant de mesurer la sécurité d'em‐ploi, les changements de propriétaire, la flexibilité numérique et la concentration syndicate. Leurs résultats s'accordent avec des donnés provenant des E‐U tels que dans Osterman (1988), et démontrent que ces nouvelles de travail ne sont pas une défense contre un environe‐ment plus hostile que jamais.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".