Now and Then: Examining Students’ Concerns About the Primary-Secondary School Transition
Bibliographic record
Abstract
Using a mixed methods approach, this study aimed to examine adolescents’ concerns about high school and the challenges they encounter after their transition to high school. Participants were recruited from 31 primary schools in metro Vancouver, British Columbia; most participants identified as female and were from a non-white ethnic background. Data was collected via self-report questionnaires from students in their last year of primary school and again 6 months after their transition to high school. The surveys used a combination of structured and unstructured questions, and thematic content analysis was used to identify the areas in which students’ express concerns about high school. Pearson chi-square tests were conducted to examine between-group gender differences in concerns about high school. Before high school, girls’ concerns were mostly centered around their social life and relationships with peers, while boys’ concerns were more varied. These findings underscore the importance of considering the unique experiences of students, by gender. In high school, boys and girls face similar challenges, with many students finding it challenging to adapt to the academic demands of high school. These findings suggest that certain key developmental assets for positive youth development, among other factors, may be lacking in schools and/or communities.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".