MétaCan
Menu
Back to cohort
Record W4416063919 · doi:10.48550/arxiv.2507.05192

Exploring Quantum Responsible Innovation efforts in Canada and the world

2025· preprint· en· W4416063919 on OpenAlexaboutno aff
Ria Chakraborty, Bruna S. de Mendonça, Katya Driscoll, Rodolfo R. Soldati, Ray Laflamme

Bibliographic record

VenueArXiv.org · 2025
Typepreprint
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Responsible Research and InnovationQuantumField (mathematics)

Abstract

fetched live from OpenAlex

The global landscape for quantum technologies (QTs) is rapidly changing, and proper understanding of their impact and subsequent regulations need to match this pace. A Responsible Innovation (RI) approach and guiding principles have been proposed to accompany this development. We examine practical efforts globally and in Canada, from industry to research to governments, and analyze the current status of quantum technological advances under the RI framework. We analyze and compare what is being done internationally, identify gaps in the Canadian strategy, propose initiatives to fill those gaps, and highlight areas where Canada is leading or where more work is needed.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.847

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.010
Science and technology studies0.0290.015
Scholarly communication0.0130.004
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.669
GPT teacher head0.435
Teacher spread0.235 · 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.

Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueArXiv.orgSame topicClimate Change Communication and PerceptionFrench-language works237,207