Employee Participation Through Non‐Union Forms of Employee Representation
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 The distinctive approach considered in this article is indirect participation through forms of non-union employee representation (NER). NER has been practiced in industry for more than a century, with considerable diversity and variation both across countries and over time. This article defines NER and provides a thumbnail sketch of its historical evolution. It describes the various forms of NER and its alternative functions. The article then synthesizes these diverse forms and functions into four distinct models/strategies of NER (called the ‘four faces’ of NER). Furthermore, it provides a brief overview of theorizing on NER. The article surveys the recent empirical literature on NER, with an emphasis on evidence regarding NER's performance and strengths and weaknesses. It ends with a brief recapitulation of the main theme; that is, that NER exhibits great diversity in form, purpose, and outcome, and that sweeping generalizations are therefore hazardous.
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 | 0.000 |
| 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 | 0.000 |
| 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