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Record W3021407300 · doi:10.1002/iir.1371

Britain and Brexit: A forecast of the future of employment protection during corporate insolvency

2020· article· en· W3021407300 on OpenAlexvenueaboutno aff
Jennifer Gant

Bibliographic record

VenueInternational Insolvency Review · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBrexitInsolvencyPosition (finance)Counterfactual thinkingPolitical scienceLaw and economicsUnanimityLawEuropean unionEconomicsPolitical economyInternational tradeFinance

Abstract

fetched live from OpenAlex

Abstract Brexit has produced a lot of uncertainties in the UK, not the least of which are the future of protections that have been derived from EU social policy Directives. Arguably, the UK's membership in the EU has pushed it further into a socially liberal and protective framework that it might not have adopted had it remained outside of the EU's sphere of influence. The question now is what direction the UK will take with regard to both the rescue culture and the social protections, both of which have been highly influenced by EU law and policy. The UK has ever been the “odd man out” in the EU, springing as it does from a significantly different legal origin than the Franco/German model at the heart of the EU. Examining the developmental path of other common law jurisdictions (America, Canada, and Australia) whose legal systems are derived from the British may be instructive in relation to the direction the UK might have taken had it not joined the EU, with a particular focus on the employment protections derived from the EU which are often applicable during insolvency and rescue procedures. An analysis of this counterfactual position may then also provide a clue or forecast as to the direction that the UK may take following Brexit.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.225
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes2
Has abstractyes

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