Making Meaning of Trust in the Organizational Setting of a School
Bibliographic record
Abstract
Recognizing that teachers are both leaders in their classrooms and colleagues in the school setting, this study focuses on the interplay of trust in the interpersonal professional relationships of teachers with their principals from the perspective of teachers. The rationale for the examination of trust is based on the assumption that trust is a key element in all human relationships and is often taken for granted because it is usually not thought about until trust fails to exist. The literature review revealed what is already known about trust, helped identify issues that merited exploration including the importance of trust, provided a solid theoretical foundation that informed the study’s methodology, and enabled me to rationalize my phenomenological approach research design. In order to come to a deeper understanding of a teacher’s experience of trust and what happens when the everyday flow of lived experience takes on a particular significance it was necessary for me to access teachers’ subjective realities. Using an Interpretive Phenomenological Analysis approach (IPA) based on the work of Smith, Flowers, and Larkin (2009), interviews were conducted using stratified purposeful sampling with 16 Alberta teachers, with varying experience levels and diverse career backgrounds. The data was organized as clusters or patterns that emerged through my interpretation of the participants’ experiences. By interrogating the meaning of the various clusters, subordinate themes were determined which expressed the essence of these clusters which then were compared and contrasted and encapsulated in superordinate themes. In previous research, trust has traditionally been considered as a monolithic variable characterized by experiences through relationships within a school (Bryk & Schneider, 2002, 2003; Kochanek, 2005). However, this study reveals that trust is best understood in a combination of two ways. First, trust is a process of holding certain perceptions and anticipation of the reliability of the other party, and secondly, trust is a product of accumulated opportunities for interaction between teachers and the principal. The findings of this study supported the viewpoint that trust in the principal was influenced by specific behaviours of the principal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.061 |
| Scholarly communication | 0.021 | 0.020 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".