Bibliographic record
Abstract
A historic turnover in the teaching profession has begun. There is no doubt that worldwide demand for teachers is on the rise and will continue to increase over the next decade. Yet many new teachers leave the profession, stating reasons such as low salaries, lack of professional opportunities and career advancement, and heavy workloads. The present study examined the concerns (in-school, external and personal) of elementary and secondary school teachers. The purpose of this research was to determine if teachers in Quebec, Canada, have concerns similar to teachers in other countries where studies are more common. This study also examined if there were any differences related to teachers' stages of teaching, level of education, and gender. Four hundred and fifty-seven teachers (335 females and 120 males) from five school boards in Quebec participated in this study. The five school boards represented urban, suburban, rural, large and small English-language boards. The instrument designed for this study was a questionnaire based on the teacher concerns identified in the literature. The questionnaire, named the Public School Teacher Concerns Questionnaire, has seven sub-scales and 64 items. Quantitative and qualitative analysis of respondent thinking reveal similar concerns regarding eight factors (37 items) derived by factor analysis: student characteristics and behaviour, teacher/administration relationship, student behaviour (non-academic), material and temporal resources, teachers control of day-to-day activities, professional development and opportunities, status of profession, and degree of non-teaching duties. Implications of the findings and directions for future research are offered.
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 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 | 0.002 | 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 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".