MétaCan
Menu
Back to cohort

Shaping the Future of Research: A perspective from early career researchers in Vancouver, Canada

2018· preprint· en· W2884137613 on OpenAlexafffundabout
Peter G. K. Clark, J. Michael McCoy, Jenny Chik, Azadeh HajiHosseini, Manuel Lasalle, Brianne A. Kent, Stefanie Vogt

Bibliographic record

VenueF1000Research · 2018
Typepreprint
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsUniversity of TorontoCanada's Michael Smith Genome Sciences CentreUniversity of British ColumbiaSimon Fraser University
FundersMichael Smith Health Research BCCentre for Blood Research, University of British ColumbiaGenome British ColumbiaWestern Canada Research Grid
KeywordsMentorshipSession (web analytics)Perspective (graphical)Political scienceEngineering ethicsPublic relationsManagementSociologyMedicineMedical educationEngineeringBusiness

Abstract

fetched live from OpenAlex

<ns4:p>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.</ns4:p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.082
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.082
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.003
Research integrity0.0010.013
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.528
GPT teacher head0.528
Teacher spread0.001 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueF1000ResearchSame topicHealth and Medical Research ImpactsFrench-language works237,207