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Record W2000534651 · doi:10.1080/03057260802681847

Identity in science learning: exploring the attention given to agency and structure in studies of identity

2009· article· en· W2000534651 on OpenAlexaff
Marie‐Claire Shanahan

Bibliographic record

VenueStudies in Science Education · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIdentity (music)Structure and agencyAgency (philosophy)SociologySocial identity approachEpistemologyPersonalityIdentity formationSocial identity theorySocial psychologyPerspective (graphical)Science educationPsychologySelf-conceptSocial sciencePedagogySocial groupComputer science

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0120.049
Scholarly communication0.0140.019
Open science0.0010.016
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.311
GPT teacher head0.569
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations157
Published2009
Admission routes1
Has abstractyes

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