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Record W4362581830 · doi:10.3390/publications11020022

Constraints on Research in Biological and Agricultural Science in Developing Countries: The Example of Latin America

2023· article· en· W4362581830 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePublications · 2023
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLatin AmericansAgricultureGlobePublicationQuality (philosophy)Political scienceEconomic growthRegional sciencePublic relationsSociologyGeographyEconomicsLawPsychology

Abstract

fetched live from OpenAlex

Science is an international effort, receiving contributions from researchers across the globe. The capacity of a country or a region to generate and publish quality research varies greatly according to the location examined. Among the factors that dictate the quantity and quality of scientific research are the availability of infrastructure and human resources, the traditions related to research endeavors, and, most significantly, local governmental support for research. There are several conditions that both individually and cooperatively limit research activities in Latin America, such as insufficient governmental support, a paucity of material and technical resources, heavy teaching loads, the absence of peer networks, and multiple constraints on publication. This commentary has been developed to discuss each of the issues that permit and, more frequently, limit biological and agricultural research endeavors in Latin America.

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.

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)0.029
metaresearch head score (Gemma)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0390.346
Science and technology studies0.0000.002
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.836
GPT teacher head0.609
Teacher spread0.227 · 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