Accepting Research: Teachers' Representations of Participation in Educational Research Projects
Bibliographic record
Abstract
Collecting data among participants belonging to a group, community or organization is a crucial step in social research. However, generally speaking, in the social sciences, the issue of access to the research field has not been widely or systematically studied and remains under-theorized. The goal of this study is to draw the participants’ perspective on the question of accepting research into their classrooms and participating in it, an object that has usually been overlooked in studies on research field access. This article presents the results of a qualitative, exploratory study aimed at documenting teachers’ representations relating to whether or not they wish to participate in research projects, when requested to do so by researchers. The analysis brought out a system comprising five categories of representations relating to participation or non-participation in an educational research project. These representations are related to 1) the teacher’s daily tasks; 2) the teacher's professional development; 3) the teacher's professional identity and professional ideal; 4) the institutional and collegial context; and 5) the teacher's responsibility toward students. We discuss these categories and their implications for further research.
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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 | 0.033 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".