Balancing the Protection of Business and Employment in Insolvency: An Anglo‐French PerspectiveJenniferGant (1st edn) (2017, Eleven International Publishing, The Hague), xxxiii +245 pp, £60, ISBN 978‐94‐6236‐755‐5
Bibliographic record
Abstract
According to the writer and philosopher George Santayana, '[t]hose who don't learn history are doomed to repeat it'.Insolvency scholars and practitioners should hold this warning in high regard, as nobody would plausibly want to go back to a time in which life imprisonment, slavery and capital punishment were common retribution for failure to pay their debts.Insolvency law has changed significantly from the collective yet retributive approach adopted in the past.Nowadays, the main emphasis lies in promoting corporate rescue (and individual rehabilitation).Nevertheless, few studies have been carried out to investigate the impact that this new goal had, and still has, on salaried workers.This book contributes to this debate by conducting a legal historical analysis of the approaches taken to balance employment protection and business rescue.Furthermore, it adopts a comparative approach, as the subject of this analysis is the evolution of English and French practice.The proposed outcome of the treatise is to formulate EU-level legal reform recommendations that will achieve a balance between employment protection and corporate rescue.This provides a timely and heterodox effort in a world where concepts such as protectionism, particularism and the 'Me-First' syndrome represent the long-established (China, Japan and Europe/Germany) or newly adopted (United States) mantras in the global politics of the leading economies.The book is structured as follows: after an introductory section, the author reports the
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".