h Learning Experience and Identity Development as a Research Assistant
Bibliographic record
Abstract
What research learning experiences do current students have as research assistants (RAs) in the Faculty of Education at Brock University? How do the experiences of research assistants contribute to the formation of a researcher identity and influence future research plans? Despite the importance of these questions, there seems to be very little research conducted or written about the experiences of research assistants as they engage in the research process. There are few resources to which research assistants or their advisors can refer regarding graduate student research learning experiences. The purpose of this study was to understand the kinds of learning experiences that 4 RAs (who are enrolled in the Faculty of Education at Brock University, St. Catharines, Ontario) have and how those experiences contribute to their identities as researchers. Through interviews with participants, observations of participants, and textual documents produced by participants, I have (a) discovered what 4 RAs have learned while engaged in one or more research assistantships and (b) explored how these 4 RAs ' experiences have shaped their identities as new researchers.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".