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Record W4382777285 · doi:10.1177/08404704231184582

Social workers’ formal and informal leadership in interprofessional primary care teams in Ontario, Canada

2023· article· en· W4382777285 on OpenAlexafffundabout
Rachelle Ashcroft, Nele Feryn, Simon Lam, Amina Hussain, Catherine Donnelly, Kavita Mehta, Jennifer Rayner, Deepy Sur, Keith Adamson, Peter Sheffield, Judith Belle Brown

Bibliographic record

VenueHealthcare Management Forum · 2023
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsWestern UniversityOntario Medical AssociationAccess Alliance Multicultural Health and Community ServicesQueen's UniversityUniversity of Toronto
FundersUniversity of Toronto
KeywordsPrimary careSocial workNursingLeadership developmentPublic relationsLeadership studiesLeadership stylePsychologyMedicinePolitical scienceFamily medicine

Abstract

fetched live from OpenAlex

The development of interprofessional teams in primary care presents opportunities for social workers to take on new leadership positions. This study seeks to describe how social workers engaged in leadership roles in primary care during the COVID-19 pandemic. A cross-sectional on-line survey was disseminated to primary care social workers across Ontario, Canada, with a total of 159 respondents. Most respondents engaged in informal leadership roles and showcased a range of leadership skills promoting team collaboration and consultations, along with adapting to virtual care transitions. Findings suggest there needs to be intentional cultivation of social work leaders through supportive environments and training. Social workers in primary care have leadership capacity and are providing leadership to their primary care teams through formal and informal means. The leadership potential of social workers in primary care teams, however, is being underutilized and can be further developed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.368
Teacher spread0.310 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2023
Admission routes3
Has abstractyes

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