Using Drama to Uncover and Expand Student Understandings of the Nature of Science
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsLydia E Carol-Ann BurkeLydia E Carol-Ann Burke (carolann.burke@utoronto.ca) is an assistant professor of science education at the Ontario Institute for Studies in Education (OISE), University of Toronto in Ontario, Canada, Alison McAvella is a secondary science and mathematics teacher with the Waterloo Region District School Board in Ontario, Canada, and Anne Wessels is a sessional lecturer in drama education at the Ontario Institute for Studies in Education (OISE), University of Toronto in Ontario, Canada.Alison McavellaLydia E Carol-Ann Burke (carolann.burke@utoronto.ca) is an assistant professor of science education at the Ontario Institute for Studies in Education (OISE), University of Toronto in Ontario, Canada, Alison McAvella is a secondary science and mathematics teacher with the Waterloo Region District School Board in Ontario, Canada, and Anne Wessels is a sessional lecturer in drama education at the Ontario Institute for Studies in Education (OISE), University of Toronto in Ontario, Canada.Anne WesselsLydia E Carol-Ann Burke (carolann.burke@utoronto.ca) is an assistant professor of science education at the Ontario Institute for Studies in Education (OISE), University of Toronto in Ontario, Canada, Alison McAvella is a secondary science and mathematics teacher with the Waterloo Region District School Board in Ontario, Canada, and Anne Wessels is a sessional lecturer in drama education at the Ontario Institute for Studies in Education (OISE), University of Toronto in Ontario, Canada.
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.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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