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Record W4309761656 · doi:10.1016/j.ssmqr.2022.100199

A midrange theory of local cross-sector action based on the actor-network theory

2022· article· en· W4309761656 on OpenAlexafffund
Angèle Bilodeau, Catherine Chabot, Nadine Martin, Mélissa Di Sante, Laurence Bertrand, Louise Potvin

Bibliographic record

VenueSSM - Qualitative Research in Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
FundersInstitute of Population and Public Health
KeywordsAction (physics)Process (computing)Empirical researchActor–network theoryValue networkFocus (optics)Value (mathematics)Management scienceComputer scienceManagementSociologyEconomicsEpistemologySocial scienceMachine learning

Abstract

fetched live from OpenAlex

Given the value of cross-sector collaborations in solving complex societal problems, experts are now recommending that research focus on documenting process–effect linkages. This paper proposes a validated midrange theory on the process–effect links of local cross-sector action on urban living conditions. The theory expands from an initial prospective study showing that changes were produced by sequences of a limited number (n ​= ​12) of transitional outcomes (TOs), derived from the analysis of empirical material informed by the Actor-Network Theory (ANT), that mark the progression of cross-sector processes toward their effects. This retrospective longitudinal multiple case (eight cases) study was conducted, using primarily case documents and additional interviews with actors involved, aimed at validating/expanding the transitional outcomes, and further anchoring them in ANT. The results confirm and enhance the inventory of TOs, reinforce their definitions, and solidify the midrange theory. This article presents the finalized inventory of TOs anchoring them both in the empirical observations from case studies and in their theoretical foundations drawn from ANT.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.016
Scholarly communication0.0060.010
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.628
GPT teacher head0.666
Teacher spread0.038 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical · Other

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

Citations9
Published2022
Admission routes2
Has abstractyes

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