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Record W2884210948 · doi:10.31265/jcsw.v11i2.140

Making sense, discovering what works…

2016· article· en· W2884210948 on OpenAlexafffundabout
Oscar E. Firbank, Janne Iren Paulsen Breimo, Johans Tveit Sandvin

Bibliographic record

VenueJournal of Comparative Social Work · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsScope (computer science)Agency (philosophy)Set (abstract data type)Public relationsSubject (documents)Core (optical fiber)Knowledge managementBusinessSociologyPolitical scienceProcess managementLaw and economicsEngineering ethicsComputer scienceEngineeringSocial science

Abstract

fetched live from OpenAlex

This paper addresses the enabling and constraining factors that underpin inter-organizational collaboration in Child Welfare and Protection services in Norway and Quebec. Characterized by different regulatory systems, but with a common drive to hierarchically promote cross-agency collaboration, these jurisdictions provide the basis for two instructive and contrasting case studies on the subject. The paper builds on meta-ethnography as a means to synthesize and translate results from separate qualitative research undertakings carried out in each place. It argues that although a core set of properties may be identified as necessary for collaboratives to operate in a successful, sustainable manner; greater attention should be paid to how these properties interact with one another on the ground, given schemes’ particular scope and scale of objectives. Moreover, regulatory provisions aimed at stimulating or mandating cross-agency networks may align with collaborative capacity in various ways, occasionally in a mutually reinforcing, but sometimes antagonistic manner. The conclusions drawn have implications for both research and policy.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.437
GPT teacher head0.560
Teacher spread0.123 · 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.

Study designOther design
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

Citations5
Published2016
Admission routes3
Has abstractyes

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