Shaping the Future of Research: A perspective from early career researchers in Vancouver, Canada
Bibliographic record
Abstract
Future of Research is an organization dedicated to championing, engaging, and empowering early career researchers (ECRs). The organization was founded in 2014 and has since inspired other groups to advocate for a more equitable and sustainable research enterprise. Here we report the findings of the Future of Research Vancouver Symposium. The goals of the Vancouver symposium were to ascertain the perspective of ECRs in Canada and to outline pathways to a sustainable future for Canadian research. The symposium had two sessions. The first session was a series of talks that were intended to prepare attendees with an informed understanding of several perspectives in the science enterprise, with a particular focus on the Canadian system. The second session was a series of interactive workshops to identify the greatest challenges facing ECRs in Canada and to propose solutions. The results of the workshops illuminated three main themes for the challenges facing Canadian ECRs: funding, mentorship, and the divide between academia and other sectors. These themes are similar to those discussed at the Future of Research symposiums in the United States, emphasizing that these issues are not isolated to Canada; however, Canadian policies are trailing behind the progress being made in other countries.
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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 | 0.027 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.101 | 0.043 |
| Scholarly communication | 0.044 | 0.006 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.009 | 0.019 |
| Insufficient payload (model declined to judge) | 0.006 | 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".