Science identity trajectories of latecomers to science in college
Bibliographic record
Abstract
Abstract This study introduces a new group of students to the postsecondary science agenda: latecomers to science. Latecomers, who enter postsecondary science through alternative routes because they are missing prerequisites, are less likely to graduate than traditional science students. Challenges to latecomers' persistence are explored through two questions: (1) What trends in science identity trajectories are latecomers to science able to construct during their first year in a college science program? (2) How are latecomers' identity trajectories constrained by or improvised with the cultural models and associated resources available in the figured world of a college science program? These questions are investigated through an analysis of educational activities, reflective writings, and interviews of nine latecomers. We view identification as analogous to velocity and demonstrate how recurring forces exerted by figured worlds and cultural models within them create patterns of acceleration towards or away from science, thus supporting or hindering persistence as identity trajectories gain or lose momentum. Findings show that latecomers' persistence was greatly constrained by two cultural models from the science program: good science students follow a paradigmatic sequence of courses and consistently earn good grades. Occasionally, latecomers improvised to resist these constraints. We illustrate our findings through three cases exemplifying inbound, outbound, and peripheral trends, offering a method of representing trajectories that may lead to new understandings of persistence. We also suggest implications for better supporting latecomers and connect this research to recent developments in the theoretical and methodological use of identity trajectories in understanding access to science. © 2013 Wiley Periodicals, Inc. J Res Sci Teach 50: 826–857, 2013
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".