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Record W180834731 · doi:10.1057/9780230595088_5

Answering the English Question

2008· book-chapter· en· W180834731 on OpenAlexaboutno aff
Alan Harding, Robert Hazell, Martin Burch, James Rees

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2008
Typebook-chapter
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDevolution (biology)Settlement (finance)English lawPoliticsGovernment (linguistics)Quarter (Canadian coin)Political sciencePopulationArgument (complex analysis)Political economyPublic administrationLawHistorySociologyEconomicsDemographyLinguistics

Abstract

fetched live from OpenAlex

Whenever devolution within the United Kingdom has been proposed, the 'English Question' has always emerged as its inevitable corollary. If there is greater home rule for the rest of the United Kingdom, so the argument goes, should a similar 'solution' not also apply to, or within, England? Should England as a whole have its own institutionalised political voice or, alternatively, should it be divided into devolved units of government? Since 1998, England has been the gaping hole in a devolution settlement that has still affected only 15 per cent of the UK population (or just over a quarter if the strengthening of citywide governance for London is deemed a devolutionary measure). Until recently, the English barely seemed to care but that may be starting to change. In the face of recent evidence that the people of Scotland and Wales have an appetite for more nationalist governments and further autonomy, there is a growing perception that the English may be 'losing out'. Clear answers to the English Question, however, seem as far away as ever; not least because of the bewildering array of ostensible solutions on offer.KeywordsRegional AssemblySelect CommitteeConservative GovernmentBewildering ArrayGaping HoleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.259
Teacher spread0.237 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations3
Published2008
Admission routes1
Has abstractyes

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