Methodology to Study Teacher Agency: A Systematic Review of the Literature
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
<p style="text-align: justify;">Teacher agency is a set of actions that a teacher takes beyond what is generally expected of them. The concept merits examination, as agency can bolster teachers’ ability to set and achieve professional development goals. To better understand how to study, and use, this relatively new concept in the academic literature, a systematic review of 164 publications written by researchers from 41 countries was conducted in order to document the research approaches used to study teacher agency, the participants whose agency was documented in a school setting, the methodology used and the type of analysis performed. The study found that teacher agency has been documented qualitatively in the form of case studies comprising interviews of a small number of individuals, with no consensus in terms of interview protocol. In most cases, the results are analyzed using emergent coding. The way that agency is documented varies but is most often underpinned by an ecological approach.</p>
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 | 0.056 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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