Identity in science learning: exploring the attention given to agency and structure in studies of identity
Bibliographic record
Abstract
This paper explores the ways in which the concept of identity has been conceptualised and studied within science education. The Personality and Social Structure Perspective is used to examine the attention paid by researchers to three levels of identity analysis: personality, interaction and social structure. Tracing the development of science identity studies and the resulting body of literature reveals that most authors have focused their attention on aspects of identity related to individual agency to the exclusion of issues of social structure. This paper argues that this attention is related to the position of communities of practice as the dominant theoretical framework for identity studies and argues that researchers need to consider broader frameworks that encourage the integration of ideas at all three levels of analysis. Broadened methodological approaches, including mixed methods, are also advocated as a way to increase consideration of the level of social structure.
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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 | 0.030 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.012 | 0.049 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.003 | 0.004 |
| 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".