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Record W2890203013 · doi:10.1111/polp.12269

Understanding Gaps in the Coexistence between Different Modes of Governance: A Case Study of Public Health in Schools in a Multilevel System

2018· article· en· W2890203013 on OpenAlexafffundabout
Viola Burau, Carole Clavier

Bibliographic record

VenuePolitics &amp Policy · 2018
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversité du Québec à Montréal
FundersMcGill UniversitySamfund og Erhverv, Det Frie Forskningsråd
KeywordsCorporate governancePublic healthMultilevel modelMulti-level governancePolitical scienceSociologyBusinessMedicineComputer scienceNursing

Abstract

fetched live from OpenAlex

Abstract Governing contemporary public services across industrialized countries typically draws on a mix of different modes of governance. The literature on governance has raised the issue of the specific coexistences between different modes of governance. The focus is on fits and clashes, whereas there is less attention on situations, where different modes of governance do not connect. The contribution of the present article is to more systematically account for the “what” and “why” of such “gaps.” What are their specific characteristics? How can their existence be explained? Based on a critical case study of supporting coordination in public health services in Québec, the article argues: that gaps in the coexistence between different modes of governance can be thought of as disconnects in the management of public services; and that this reflects a de facto lack of governance capacity to connect different modes of governance to each other.

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)0.010
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.775

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0210.015
Scholarly communication0.0070.004
Open science0.0020.008
Research integrity0.0030.004
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 head0.578
GPT teacher head0.522
Teacher spread0.056 · 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

Citations3
Published2018
Admission routes3
Has abstractyes

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