Advanced Placement Environmental Science and the Curriculum and Community Enterprise for Restoration Science (CCERS) Project in the New York City High School
Bibliographic record
Abstract
This paper explores the issue of social justice through the lens of equitable access to Advanced Placement courses inthe City of New York High Schools, with focus on Advanced Placement Environmental Science. A criticalcomponent of the Advanced Placement Environmental Science course is the incorporation of environmentalfieldwork. The National Research Council (2014) suggest that field stations are important for STEM education andprovide opportunities to engage students in the natural environment and get them excited about science. Through theCurriculum and Community Enterprise for Restoration Science, an NSF funded opportunity, students in theAdvanced Placement Environmental Science course are integrating their field station work in Oyster Restoration inthe New York City Harbor. These interactions with the environment offer unique experiences which engagemarginalized students in both rigorous coursework and affords equity in science learning. In turn, it affords allstudents the opportunity for upward mobility and increased career opportunities in the area of STEM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".