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Record W4220866992 · doi:10.1097/acm.0000000000004257

Breaking Borders: How Barriers to Global Mobility Hinder International Partnerships in Academic Medicine

2021· article· en· W4220866992 on OpenAlexaff
Dawit Wondimagegn, Lamis Ragab, Helen Yifter, Monica Wassim, Ahmed Rashid, Cynthia Whitehead, Deborah Gill, Sophie Soklaridis

Bibliographic record

VenueAcademic Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsCentre for Addiction and Mental HealthWomen's College Hospital
Fundersnot available
KeywordsRealmGlobal healthPolitical sciencePoliticsPublic relationsSociologyInequalityNarrativeEconomic growthHealth careLawEconomics

Abstract

fetched live from OpenAlex

This article describes the authors’ personal experiences of collaborating across international borders in academic research. International collaboration in academic medicine is one of the most important ways by which research and innovation develop globally. However, the intersections among colonialism, academic medicine, and global health research have created a neocolonial narrative that perpetuates inequalities in global health partnerships. The authors critically examine the visa process as an example of a racist practice to show how the challenges of blocked mobility increase inequality and thwart research endeavors. Visas are used to limit mobility across certain borders, and this limitation hinders international collaborations in academic medicine. The authors discuss the concept of social closure and how limits to global mobility for scholars from low- and middle-income countries perpetuate a cycle of dependence on scholars who have virtually barrier-free global mobility—these scholars being mainly from high-income countries. Given the current sociopolitical milieu of increasing border controls and fears of illegal immigration, the authors’ experiences expose what is at stake for academic medicine when the political sphere, focused on tightening border security, and the medical realm, striving to build international research collaborations, intersect. Creating more equitable global partnerships in research requires a shift from the current paradigm that dominates most international partnerships and causes injury to African scholars.

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)0.003
metaresearch head score (Gemma)0.017
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.087
GPT teacher head0.418
Teacher spread0.331 · 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 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

Citations15
Published2021
Admission routes1
Has abstractyes

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