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Record W2069561046 · doi:10.1371/journal.pntd.0002568

Canada's Neglected Tropical Disease Research Network: Who's in the Core—Who's on the Periphery?

2013· article· en· W2069561046 on OpenAlexafffundabout
Kaye Phillips, Jillian Clare Köhler, Peter Pennefather, Halla Thorsteinsdóttir, Joseph Wong

Bibliographic record

VenuePLoS neglected tropical diseases · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersCanadian Health Services Research Foundation
KeywordsGeographyNeglected tropical diseasesRegional sciencePolitical scienceEconomic growthSocioeconomicsMedicineDiseaseSociologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: This study designed and applied accessible yet systematic methods to generate baseline information about the patterns and structure of Canada's neglected tropical disease (NTD) research network; a network that, until recently, was formed and functioned on the periphery of strategic Canadian research funding. METHODOLOGY: MULTIPLE METHODS WERE USED TO CONDUCT THIS STUDY, INCLUDING: (1) a systematic bibliometric procedure to capture archival NTD publications and co-authorship data; (2) a country-level "core-periphery" network analysis to measure and map the structure of Canada's NTD co-authorship network including its size, density, cliques, and centralization; and (3) a statistical analysis to test the correlation between the position of countries in Canada's NTD network ("k-core measure") and the quantity and quality of research produced. PRINCIPAL FINDINGS: Over the past sixty years (1950-2010), Canadian researchers have contributed to 1,079 NTD publications, specializing in Leishmania, African sleeping sickness, and leprosy. Of this work, 70% of all first authors and co-authors (n = 4,145) have been Canadian. Since the 1990s, however, a network of international co-authorship activity has been emerging, with representation of researchers from 62 different countries; largely researchers from OECD countries (e.g. United States and United Kingdom) and some non-OECD countries (e.g. Brazil and Iran). Canada has a core-periphery NTD international research structure, with a densely connected group of OECD countries and some African nations, such as Uganda and Kenya. Sitting predominantly on the periphery of this research network is a cluster of 16 non-OECD nations that fall within the lowest GDP percentile of the network. CONCLUSION/SIGNIFICANCE: The publication specialties, composition, and position of NTD researchers within Canada's NTD country network provide evidence that while Canadian researchers currently remain the overall gatekeepers of the NTD research they generate; there is opportunity to leverage existing research collaborations and help advance regions and NTD areas that are currently under-developed.

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)0.011
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.989
Threshold uncertainty score0.665

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.055
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0130.035
Science and technology studies0.0100.004
Scholarly communication0.0100.003
Open science0.0020.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.046
GPT teacher head0.295
Teacher spread0.250 · 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 designObservational
DomainEvaluation
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

Citations18
Published2013
Admission routes3
Has abstractyes

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