From “Taking Orders” to Being a “Self-starter”: Research Assistants and Postdoctoral Fellows’ Skill Development in Large Collaborative Research Projects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Like many nations, Canada competes on the global market as a knowledge-based economy.As such, the country needs employees with skills in self-direction, communication, adaptability, critical thinking, project management, and collaboration as well as technical skills and content knowledge to innovate and compete with other post-secondary institutions, companies, organizations, and countries (Bilodeau; Mitacs; Niemczyk, Expanding; SSHRC, "Report").However, while there has been increasing use of collaborative projects in graduate course work, graduate and postdoctoral training remains primarily solitary in nature, which means limited opportunities for these individuals to fully develop these skills (Barry et al.; Bohen and Stiles).But what skills can a graduate student and postdoctoral fellow develop through their course work and associated training in school and beyond?What are the best ways to gain these?One possible avenue of experience is as graduate research assistants (RAs) and postdoctoral fellows (postdocs)on faculty research projects (Niemczyk, "Preparing").Students and postdocs can undertake a variety of research tasks, such as literature reviews, data collection and analysis, research write ups, experiments, and others.These faculty research projects are also becoming more collaborative in nature as research questions become more complex and require an approach that brings together teams of people with different skill sets and knowledge (He and Jeng; Kosmützky).This means that RAs and postdocs can gain experience in collaboration and project management as well as important content knowledge and methodologies (SSHRC, "Report").These opportunities prepare students and postdocs for careers in the academy as well as private, public, and nonprofit sectors.This context raises questions about the type of experiences that RAs and postdocs gain within collaborative research projects funded through faculty researchers' grants.There is little research on the research assistance and postdoctoral training as "educational spaces where theory meets practice" (Niemczyk, Expanding 1).What training do they receive?How do they develop skills needed for the particular research project and employment beyond it?This paper will contribute to this discussion by examining the lived experience
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it