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Record W1994091968 · doi:10.1080/02673037.2013.803045

The Dynamics of Policy-Making under UK Devolution: Social Housing in Northern Ireland

2013· article· en· W1994091968 on OpenAlexfundno aff
Jenny Muir

Bibliographic record

VenueHousing Studies · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsDevolution (biology)Public administrationTechnocracyPolitical sciencePoliticsPolitical economyCorporate governanceCitizenshipSettlement (finance)Social policyIdeologySociologyEconomicsLawPayment

Abstract

fetched live from OpenAlex

Housing policy formation under the United Kingdom's devolution settlement is currently under-researched and insufficiently understood. This article uses the example of social housing policy-making in Northern Ireland to reflect on its impact. Five factors with the potential to influence post-devolution policy-making are identified: common UK citizenship and ideology, policy networks, the political process, the mechanics of devolution and membership of the European Union. A post-devolution review of social housing policy in Northern Ireland is followed by a discussion of three key issues from the 2007 to 2011 administration: governance, procurement of new social housing, and ‘shared space’ and a shared future. Interviews with policy-makers indicate that 2007–2011 marked the beginnings of a trend away from the technocratic domination of officials towards greater intervention and policy ownership by politicians, but that the significance of this should not be overstated. The implications for multi-level and multi-jurisdictional policy-making in devolved and federal states are considered.

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)0.007
metaresearch head score (Gemma)0.011
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 score0.242
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.012
Scholarly communication0.0100.005
Open science0.0010.011
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.264
Teacher spread0.228 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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