Designing Frameworks for Authentic Equity in Science Teaching and Learning: Informal Learning Environments and Teacher Education for STEM
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
Abstract In order to advance authentic equity in science education, it is salient to have frameworks that allow educators and researchers to design learning environments, activities, and research agendas that centers students’ strengths in order for them to achieve full participation in science. As such it is important to consider the social identities of science education stakeholders—teachers and students—in teacher education. However, as identity is complex, it requires research approaches that elucidate not only the nuances of teacher identity but also the complexities of science teaching and learning environments. This article describes a collaborative research project that aimed to unpack the relationship between teacher identity and learning to teach. It outlines the collaborative process of theory building that includes teacher participants and the research team and how the framework for teacher education emerged that considers the various aspects of designing equitable and liberatory science learning.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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 it