Trajectories of Educational Aspirations Through High School and Beyond: A Gendered Phenomenon?
Bibliographic record
Abstract
Growth curve modeling was utilized to examine change in the educational aspirations of adolescents from early high school through to three years beyond high school, as a function of gender and other adolescent characteristics. Significant gender effects were found for level of education aspired to, rate of growth, and degree of acceleration: boys’ aspirations were lower in early high school, accelerated at a faster pace to peak above girls’ aspirations by the end of high school, and dropped more steeply so that, by the post-high school period, educational aspirations were equivalent across genders. Gender also interacted with Grade 9 achievement in determining educational trajectories. Finally, the perception that one faces barriers in educational attainment was found to significantly influence rate of growth and acceleration, indicating that change in aspirations over time differs between people who see barriers to their education and people who do not, independently of gender. Implications of these results for promoting students’ educational aspirations are discussed. Keywords: Gender, high school, educational aspirations
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".