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Record W2224262339 · doi:10.3138/ptc.2014-95

Perceptions of Leadership: Comparing Canadian and Irish Physiotherapists' Views

2016· article· en· W2224262339 on OpenAlexvenueaboutno aff
Emer McGowan, Gillian Martin, Emma Stokes

Bibliographic record

VenuePhysiotherapy Canada · 2016
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsIrishPerceptionDeclarationMedicineNorthern irelandNursingPhysical therapyPsychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

Purpose: To contribute to the growing body of research on leadership in physiotherapy by comparing leadership-related perceptions of physiotherapists in Ireland and in Canada. Methods: This article compares the results of a survey of Canadian physiotherapists with those of the same survey administered to Irish physiotherapists. The results of both studies have previously been reported and are used here to allow a cultural comparison of the perceptions of physiotherapists. The present study used two-portion Z-tests to compare the percentage of physiotherapists in Ireland who self-declared as a leader with the percentage of physiotherapists in Canada who did so. Results: Physiotherapists in both Ireland and Canada most often rated communication and professionalism as extremely important characteristics. Physiotherapists in Canada were more likely than those in Ireland to perceive themselves as leaders (Z=2.67, p < 0.05; 95% CI: 1.33, 9.87). Factors associated with self-declaration as a leader differed between the two countries. Conclusion: Physiotherapists in Canada and Ireland showed both similarities and differences in their perceptions of leadership characteristics. Results from this study may aid the development of future leadership training programmes specifically targeted at physiotherapists.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.041
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.161
GPT teacher head0.455
Teacher spread0.294 · 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 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

Citations12
Published2016
Admission routes2
Has abstractyes

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