Bibliographic record
Abstract
This article concerns the manner in which the European Union Information and Consultation of Employees (ICE) Directive has been implemented in the UK in the harsh corporate conditions of restructuring, redundancy and site closure. Drawing on interview and documentary evidence from six case companies (Peugeot-Citroën, General Motors, Prudential, Aviva, Marconi, Rolls-Royce), the article exposes major fault lines in the effectiveness of the UK’s ICE Regulations to provide even limited protection for employees who were presented with redundancy as a fait accompli. Contrary to management claims, ICE arrangements have not provided additional levels of representation either to complement unions or to fill the “representation gap” left by declining coverage. The failure to consult raises broader questions on the wider political and legislative environment in the UK.
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.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.047 |
| Scholarly communication | 0.011 | 0.027 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".