Teachers’ psychological functioning in the workplace: Exploring the roles of contextual beliefs, need satisfaction, and personal characteristics.
Bibliographic record
Abstract
The purpose of the current study was to provide a greater depth of knowledge about teachers’ psychological functioning at work—including the contextual, basic psychological need satisfaction and personal factors relevant to this. We examined the extent to which perceived autonomy support predicts basic psychological need satisfaction and, in turn, whether need satisfaction predicts teachers’ perceptions of well-being, motivation, job satisfaction, and organizational commitment. Participants were 485 Canadian school teachers (76% female) who completed an online questionnaire. After confirming the measurement model with factor analysis, the hypothesized model was tested using structural equation modeling. Findings indicated that perceived autonomy support positively predicted need satisfaction, and, in turn, need satisfaction predicted the work-related perceptions. Of particular importance were the differing roles played by the basic psychological needs in predicting each of the work-related perceptions. Additional analyses revealed that well-being and motivation played key mediating roles in how need satisfaction was associated with job satisfaction (but less so with commitment) and that teachers’ personal characteristics played minor moderating roles in influencing how teachers’ workplace beliefs and perceptions were associated. Together, the study’s findings enable a greater depth of understanding about teachers’ psychological functioning at work, which is important for healthy teachers and effective teaching and learning. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".