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Record W2181031308 · doi:10.3138/ptc.2014-48

What Makes a Leader: Identifying the Strengths of Canadian Physical Therapists

2015· article· en· W2181031308 on OpenAlexaffvenueabout
Zachary Chan, Ashley Bruxer, Jonathan Lee, Katelin Sims, Matthew Wainwright, Dina Brooks, Laura Desveaux

Bibliographic record

VenuePhysiotherapy Canada · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhysical therapistPhysical medicine and rehabilitationComputer sciencePhysical therapyMedicine

Abstract

fetched live from OpenAlex

PURPOSE: To identify the personal strengths of Canadian physical therapists who hold leadership positions and compare them with the strengths of Canadian physical therapists who do not occupy positions of leadership. METHODS: A quantitative, cross-sectional online survey was distributed to registered Canadian physical therapists. We used the Clifton StrengthsFinder to evaluate 34 characteristics and determine which characteristics described a participant's strengths. Population demographics and leadership strengths were described via frequency distributions and percentages; chi-square analyses and Fisher's exact tests were used to compare differences between groups. RESULTS: Of 173 physical therapists who completed the survey, 108 occupied a position of leadership, and 65 did not. Those in the leader group had significantly more experience and achieved a higher level of education. Leaders most frequently exhibited the strengths of learner, achiever, responsibility, input, and strategic, whereas non-leaders most frequently displayed strengths of learner, achiever, input, relator, and harmony. Leaders were significantly more likely than non-leaders to possess the achiever strength. Gender, level of education, and years of experience did not significantly influence which strengths were present in the leadership profile. CONCLUSIONS: There is substantial overlap between leaders and non-leaders in terms of leadership profiles. Future research should investigate whether leadership strengths vary depending on the leadership position occupied and whether leadership development initiatives promote leadership strengths.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.997

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 head0.148
GPT teacher head0.487
Teacher spread0.338 · 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 designNot applicable
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

Citations22
Published2015
Admission routes3
Has abstractyes

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