Overview of Current After School - OST STEM Programs for Girls
Why this work is in the frame
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Bibliographic record
Abstract
Historically, there has been a gender gap within the STEM pipeline, resulting in the underrepresentation of women in STEM fields. Current efforts, both within and outside of educational institutions, have been developed to target girls’ specific needs with the aim of supporting girls' interest and engagement in STEM. The following paper examines the social and cultural factors that perpetuate the gender gap in STEM. It also provides a review and critique of six existing Canadian Out of School Time (OST) STEM programs and the principles used in their development and implementation. Conclusions from this review suggest that OST programs, when developed using best practices, may play a crucial role in encouraging girls to pursue a STEM career. Four primary best practices include: social and collaborative learning, topics related to girls' interests, development of STEM identity, and length of the program (for example, programs done over a longer period of time are generally more effective than programs completed over a shorter duration). Although the COVID-19 pandemic has caused some of these programs to migrate online, these four promising practices transcend face-to-face versus online boundaries. As a result, programs should continue to follow these pedagogical approaches to foster girls' interests in STEM. Keywords: gender inequality, out of school time programs, social learning, STEM education, STEM programming
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it