10. Utilizing Science Outreach to Foster Professional Skills Development in University Students
Bibliographic record
Abstract
Students seek unique experiences to obtain and enhance professional development skills and to prepare for future careers. Through the Let’s Talk Science Partnership Program (LTSPP), a voluntary science outreach program at University of Toronto Scarborough, students are given the opportunity to continually improve on skills which include: the “3 Cs” (creativity, communication, cooperation), and leadership and organization skills through hands-on activities in classrooms and community centres across the city and in isolated rural communities. Volunteers serve as mentors, and frequently transfer knowledge related to their research and coursework to youth. Here, we present results from surveys on current and past volunteers (2004-2010). Volunteers were asked to evaluate the value of the skills they obtained through science outreach, and the relevance of those skills to obtaining current work and achieving long-term career goals. Respondents commented on the effectiveness of the skills they obtained and ranked the transferable skills. We show that volunteer work through LTSPP largely improves their communication and confidence skills. As well, students identified clear links between science outreach and professional goals, and highly recommended LTSPP to others.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".