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Record W7132901085

The Influence of Trust on Teachers' Inclination to Exercise Informal Leadership

2012· dissertation· en· W7132901085 on OpenAlexaffabout
Mark Baxter

Bibliographic record

VenueTSpace · 2012
Typedissertation
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHonestyOpenness to experienceEliteTrustworthinessWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

This research focuses on the role that trust and its component facets - competence, benevolence, openness, reliability and honesty (Tschannen-Moran, 2004) - play in affecting teachers’ inclination to exercise informal leadership. Teachers in the elementary sections of three elite urban independent schools in Ontario nominated colleagues as informal teacher leaders in their schools and a total of nine teachers, who received multiple nominations, were selected for interview. The interviews unexpectedly revealed two distinct experience-based groupings of informal teacher leaders, with the members of the two groups exhibiting distinctive leadership behaviours. Trust was an important factor affecting all of the teacher leaders’ inclination to exercise informal leadership, but the two experience-based groups revealed different patterns of emphasis for the trust facets (for example, the less-experienced leaders highlighted benevolence above all other facets while the more-experienced teachers considered openness to be the most important). The findings have implications for the ways in which schools can promote the exercise of informal leadership.

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)0.002
metaresearch head score (Gemma)0.018
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: Other · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.189
GPT teacher head0.469
Teacher spread0.280 · 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
GenreOther

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
Published2012
Admission routes2
Has abstractyes

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