The Curriculum and Community Enterprise for Restoration Science Making STEM Accessible, Equitable and Environmentally Relevant
Bibliographic record
Abstract
Underrepresented and marginalized students have challenges when connecting their personal identities to STEM identities. This has a direct impact on the post-secondary educational and career choices of these students. Some factors which contribute to the disenfranchisement of marginalized students include inequity in academic preparation, students’ lack of self-efficacy and self-identity in STEM, students’ lack of connection to the STEM curriculum and students’ lack of role models and mentors. Although the opportunities in the STEM workforce are abundant and lucrative, students who identify as students of color, female and/or English language learners are poorly represented in the STEM professions. Through the CCERS STEM + C Program, students are asked to expand their STEM identity through near-peer mentoring, encounters with STEM experts and individual STEM Research projects that are focused on the environmental restoration of New York Harbor, its watershed and the native oyster population.
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How this classification was reachedexpand
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 | 0.007 | 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 | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".