*Teacher Administrator Relationship; *Women Administrators
Bibliographic record
Abstract
This paper presents findings of a study that determined relative differences in male and female teachers' perceptions of male and female principals ' intentions in the communication process. Data were derived from administration of the Leadership as Social Control (LASC) Model to 397 teachers in the Calgary School District. They reported their perceptions of 20 principals (10 male and 10 female). Three orientations (personal, official, and structural) and three motivations (authority, positive power, and negative power) of leader communication by gender were examined. Findings indicate that male and female teachers perceived female principals as communicating their authentic values and verbal expressions of expectations more than male principals. Principal gender affected teachers ' perceptions more than teacher gender. All teachers perceived that female principals paid more attention to their teachers ' work, whether positive or negative attention. A link was found to exist among teachers ' perception of principal effectiveness, a feeling of closeness to the principal, and the degree of attention that principals give teachers. It is recommended that male principals communicate interest in teachers ' lives. Seven tables and two figures are included. (LMI) Reproductions supplied by EDRS are the best that can be made from the original document. tr.*. oenarrompa OF EDUCATION
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.005 |
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".