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Record W2887789865

Canadian Universities: Emerging Hubs for International Parliamentary Research and Training

2018· article· en· W2887789865 on OpenAlexvenueaboutno aff
Rick Stapenhurst, Phoebe Zamanuel

Bibliographic record

VenueCanadian parliamentary review · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Political scienceWork (physics)Public administrationKingdomLibrary scienceManagementGeographyEngineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

Canadian universities have recently emerged as important centres in applied parliamentary research and training, joining universities in Australia, the United Kingdom and elsewhere. This article reviews the growth of these research and training programs at three institutions – McGill University, Universite Laval and the University of Ottawa – over the past five years. It also points to possible future areas of work, which will allow parliaments elsewhere to learn from Canada’s experience, and vice versa.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score0.996

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.018
Science and technology studies0.0120.004
Scholarly communication0.0130.004
Open science0.0030.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.371
GPT teacher head0.523
Teacher spread0.151 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2018
Admission routes2
Has abstractyes

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