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Spaces of influence in decentralised governance systems: a comparison of substate civil society networks and politics in the United Kingdom and Canada

2025· article· en· W4410947255 on OpenAlexaffabout
Sioned Pearce, Christala Sophocleous, Deena White, Rachel Laforest, Karine Levasseur, Sid Frankel

Bibliographic record

VenueVoluntary Sector Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsUniversity of ManitobaQueen's UniversityUniversité de Montréal
FundersWales Institute of Social and Economic Research and Data
KeywordsCivil societyPoliticsCorporate governancePublic administrationKingdomPolitical sciencePolitical economySociologyLawEconomicsManagement

Abstract

fetched live from OpenAlex

Here we explore three case studies, Wales, Quebec and Manitoba, to examine how changes in multilevel governance affect the strategies and the operating environment of civil society organisations (CSO).1 Every multilevel system of governance has considered ways to share political responsibility for social service delivery, vertically between levels of government and horizontally with non-state organisations. Wales, Quebec and Manitoba all have subnational authority over social policy as a result of devolution (United Kingdom) and constitutional arrangements (Canada). Comparing their experiences suggests shifts in the locus of governance that disrupt established patterns and create opportunities for the redesign of governance arrangements. New dynamics are contingent upon the way that CSOs navigate new structures to position themselves in the policy arena.

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)0.003
metaresearch head score (Gemma)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.872

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0120.011
Scholarly communication0.0110.002
Open science0.0010.005
Research integrity0.0010.001
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 head0.047
GPT teacher head0.367
Teacher spread0.321 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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