Bibliographic record
Abstract
This article reviews the English-speaking literature on Spanish and German industrial relations published in the top 10 journals in this field between 2000 and 2010. The analysis contributes to the ongoing debate about the relevance of industrial relations by establishing the state of the art in research on Spain in comparison to Germany. Following this assessment we then ask whether existing research on Spain is well situated to orient policymakers. The consequences of either normative or normative-free research have largely been overlooked; our discussion expands on two contrasting positions: suggesting a move away from ideology in research (Mitchell, 2001) or recommending normative assumptions as a necessary precondition (Frege, 2007) in the context of Spain. Our findings reveal a greater convergence in research regarding its restricted multidisciplinary character, its focus on the international level and a strong emphasis on empirical, quantitative work with analysis conducted at various levels. At the same time, some path dependency continues to exist, particularly concerning the active participants in research and the subjects for investigation. The results point to deficiencies in research on Spanish industrial relations. We conclude by advocating an openly stated, normative base in industrial relations research to guide policymakers in Spain. While an evidence-based approach in policy making is desirable, normative choices are highly consequential and should feature in research in order to avoid a “democratic shock” in Spain.
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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 | 0.114 | 0.165 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.011 | 0.020 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.038 | 0.034 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.016 | 0.008 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".