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Record W7118855841 · doi:10.5281/zenodo.18155347

Ethics Brief: Achieving Equitable Research Partnerships by Facilitating Visas for Short-Term Researcher Mobility

2025· article· W7118855841 on OpenAlexaff
Doris Schroeder, Thomas Pogge, Nadia Kornioti, Joshua Kimani, François Bompart, Klaus M. Leisinger, Stephanie Laulhe Shaelou, Nandini Kumar, Thomas Nyirenda, W. J. Zhu, Ock Joo Kim, Kate Chatfield

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsEuropean unionAgency (philosophy)Work (physics)State (computer science)Funding AgencyResponsible Research and InnovationPublic funding

Abstract

fetched live from OpenAlex

Addressing humanity's challenges through research will only work if scientists can collegially share their ideas, knowledge, and research results. In this brief, we focus on the short-term mobility of scientists. We advocate for fast, unbureaucratic, low-cost, low-burden, short-term mobility visas, as the current visa requirements significantly impede scientific exchange. We explicate this ethically, according to the fourt values of Fairness, Respect, Care and Honesty. -- Funded by the European Union. UK participants in Horizon Europe Project PREPARED are supported by UK Research and Innovation grant number 10048353 (University of Central Lancashire). Swiss participants in Horizon Europe Project Prepared are supported by the State Secretariat for Education, Research and Innovation (SERI). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Research Executive Agency or UKRI or SERI. Neither the European Union nor the granting authority nor UKRI or SERI can be held responsible for them.

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)0.063
metaresearch head score (Gemma)0.081
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.653
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0630.081
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0160.005
Scholarly communication0.0030.001
Open science0.0040.006
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0110.002

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.

Opus teacher head0.253
GPT teacher head0.418
Teacher spread0.165 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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