The Effects of Context and Experience on the Scientific Career Choices of Canadian Adolescents
Bibliographic record
Abstract
This study explored the differential utility of contextual and experiential factors in the prediction of scientific career aspirations. Specific propositions based on the Lent et al. ( 1994) socialcognitive model of career choice were also examined. Data were obtained from a Canadian national subgroup (n=--3,306) of adolescents (13-19 years) who participated in the National Youth and Science Fair Project Study (NYSPS). Multivariate logistic regression analyses indicated that family background, scientific learning experiences, science self-efficacy measures, outcome expectancies, and scientific interests contributed significant unique variance to the prediction of scientific career choice. Results of a final model revealed that students aspiring for a career in the sciences were more likely than their peers to be male, senior students, have higher grades in science, more interest in science, and expect their science courses to be useful to their future career. Scientific self-efficacy and outcome expectancies were found to have direct effects on choice goals. Outcome expectancies also had an indirect effect on choice goals through scientific interests. Scientific interests had a significant direct effect on choice goals. Implications for career development/choice theory and practice arc discussed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".