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Record W2283832495 · doi:10.1177/0170840615622067

Contestation about Collaboration: Discursive Boundary Work among Professions

2016· article· en· W2283832495 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOrganization Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsUniversity of AlbertaUniversity of OttawaHEC Montréal
Fundersnot available
KeywordsFraming (construction)CentralityBoundary-workSociologyEpistemologyPublic relationsPolitical scienceSocial scienceEngineering

Abstract

fetched live from OpenAlex

We examine how professions responded to a potential change in jurisdictional boundaries by analyzing the written submissions of five professional associations in reaction to a government proposal to strengthen interprofessional collaboration, relating these responses to the professions’ field positions. We identify four foci for framing used by the professions to discursively develop their boundary claims: (1) framing the issue of interprofessional collaboration (issue framing), (2) framing of justifications for favored solutions (justifying), (3) framing the profession’s own identity (self-casting), and (4) framing other professions’ identities (altercasting). We find that professions employed these foci differently depending on two dimensions of their field positions – status and centrality. Our study contributes to the literature by identifying distinctive ways through which the foci for framing may be mobilized in situations of boundary contestation, and by theorizing how field position in terms of status and centrality influences actors’ framing strategies.

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.

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
gemmaScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.520
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.062
GPT teacher head0.402
Teacher spread0.340 · 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