“Anybody can do science if they're brave enough”: Understanding the role of science capital in science majors' identity trajectories into and through postsecondary science
Bibliographic record
Abstract
Abstract This article reports on research investigating the experiences and resources that make science thinkable for undergraduate science majors as they engage in postsecondary science contexts. We regard these experiences and resources as contributing to science majors' science capital, and we suggest that science capital accumulates over time across identity trajectories. Using a multiple case study approach, we characterize seven undergraduate science majors' identity trajectories that they narrate through their stories of experiences with science in school, out of school and into postsecondary education. We examine how they navigate sources of science capital (e.g., families, science outreach), and the value they attribute to their science capital once they enter science programs in university. We also consider how their access to science capital influences their reasons for engaging in science outreach. To characterize students' movements into postsecondary education, and their experiences in postsecondary science, we crafted three identity trajectories: the “expected trajectory,” “persistent trajectory” and the “new directions trajectory.” These trajectories helped us to examine how science majors' identities mediate their perceptions of the use and exchange values of their science capital and the doxa of science that they legitimate. This study contributes to our understanding of how science capital operates along identity trajectories into postsecondary science, and demonstrates that simply having access to resources that contribute to students' accumulation of science capital is not sufficient for sustained engagement in science.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".