Bibliographic record
Abstract
This chapter presents a limited comparative analysis in order to explore the potential transferability of the multidimensional framework. It considers five countries, namely, China, France, Germany, Japan and US. Whereas a single Chinese union projects a ‘true general union identity’ and operates in parallel with the Communist Party, the multiplicity of competing French unions project identities that can only be understood with the addition of political and religious sources. Although most German unions project industrial identities, for some a religious or professional component is required. The multi-layered structure of Japanese union organisation includes unions that project ‘organisational union identities’ in the corporate sector and ‘industrial union identities’ in the public sector and public services. The majority of US unions project occupational and/or industrial identities, although many also have binational identities, with membership territories incorporating the US and Canada. In contrast the Teamsters and IWW project ‘general union identities’ and a more militant version of ‘protest union identity’. Whilst the chapter concludes that the multidimensional framework is broadly applicable to unions in other countries it identifies that additional sources of identity are needed for comparative analysis.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".