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Record W2144244468 · doi:10.1017/s1744552310000273

Ambivalence towards law: Business Improvement Associations, public disorder and legal consciousness

2010· article· en· W2144244468 on OpenAlexaff
Prashan Ranasinghe

Bibliographic record

VenueInternational Journal of Law in Context · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDisenchantmentAmbivalenceReverenceLegal consciousnessConsciousnessLawPhilosophy of lawSociologyPolitical scienceLaw and economicsSocial psychologyPsychologyPublic law

Abstract

fetched live from OpenAlex

Abstract This article examines the ways the business community – here operationalised through Business Improvement Associations (BIAs) – thinks about and makes sense of the Law and the legal system, its legal consciousness, in other words. I suggest that the way BIAs think about and make sense of the Law is best described as ambivalent, ranging from reverence to disenchantment: on the one hand, the Law is (like) God, but on the other, the Law is also a source of angst, frustration, hopelessness and powerlessness. Drawing on the analytical framework of legal consciousness, I suggest, provides a good platform from which to explore whether the ‘haves’ come out ahead, and what coming out ahead might mean and look like to them. Equally, the ambivalence towards law shows that the ways the ‘haves’ make sense of the Law might not always be that antithetical to the way the ‘have-nots’ make sense of the Law.

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0160.084
Scholarly communication0.0200.009
Open science0.0010.015
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.309
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations12
Published2010
Admission routes1
Has abstractyes

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