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Record W7133042497

Impact of Multi-level External Factors on Role Identities of Community Pharmacy Owners/Managers and Service Provision in Ontario, Canada

2023· dissertation· W7133042497 on OpenAlexaboutno aff
Hyunjin Woo

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacyNegotiationCommunity pharmacyPharmacy practiceThematic analysisIdentity (music)Service (business)Health care
DOInot available

Abstract

fetched live from OpenAlex

This qualitative paper aims to explore how multi-level external factors influence the role identity of pharmacy owners/managers and pharmacy service provision. Data were collected from 10 semi-structured interviews and 14 online questionnaires from pharmacy owners/managers at community pharmacies in Ontario, Canada, and were analyzed through thematic analysis. In addition, documents were reviewed to explore the pharmacy field in Ontario. Ten role identities have been found, each showing different degrees of adherence to four institutions: profession, corporation, market, and state. Participants had to negotiate between competing demands created by the four institutions, which were likely to have arisen from a mismatch between policies and the system in the pharmacy field regarding how pharmacy services are understood, financed, and delivered. The findings suggest the importance of understanding healthcare professionals as being socially embedded and creating a coherent system that can facilitate professionals in achieving policy goals and professional ideals.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.065
Threshold uncertainty score0.471

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0170.009
Scholarly communication0.0050.001
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.229
GPT teacher head0.470
Teacher spread0.241 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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