Work in Progress: Evaluation of Canadian high school girls' perception of CSET using a play
Bibliographic record
Abstract
Women have always been under-represented in Canadian engineering faculties despite all of the efforts to attract them to this profession. Historically, less than 25% of all undergraduate students in Canadian engineering faculties are women. To counteract this phenomenon, it is essential to promote women's participation in the fields of CSET. An educational tool has been developed to promote and heighten knowledge of CSET fields for Grade 9 and 10 girls. This tool is a theatrical play that presents different professions which are linked to CSET in a humorous manner using lay language. The project evaluates Grade 9 and 10 students' perception of CSET, and validates whether the educational tool can change those perceptions. The methodology uses individual interviews of 24 students from two high schools to ask about their perception of CSET fields. The validation was done by a qualitative and quantitative analysis of the data collected. Preliminary results shows that after the presentation of the theatrical play, many girls mentioned that the play made them think more about their career choices and some of them acknowledged that CSET disciplines could be an option for those who already have an interest in science and in engineering.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".