Male ECE Students in Post-secondary Classrooms: Enrolment and Retention
Bibliographic record
Abstract
This study examines the underrepresentation of male Early Childhood Education (ECE) students in post-secondary classrooms. Through the implementation of a mixed methods design, quantitative data on student enrolment and graduation rates were collected (N=3009) and discussed in the context of the perspectives of male interview participants (n=4). Data collected from a large Ontario college demonstrated that males comprised an average of only 5.4% of students enrolled in the ECE program over an eight-year timespan, and of that demographic (n=159), only 30.8% of male students graduated. This rate was signifcantly lower than that seen in female students during the same time period. Interviews revealed that male ECE students face a number of deterrents, from bias to gender imbalance in post-secondary classrooms and placement settings. However, these variables can potentially be mitigated through protective factors, for example, connections with faculty, motivation and self-effcacy. In light of the continued low enrolment for male ECE students, and recent downward trend in graduation rates, research-based support strategies are recommended to help increase enrolment and retention.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".