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Ethics Review on Externally- Sponsored Research in Developing Countries

2009· book-chapter· en· W2483879705 on OpenAlexaff
Alireza Bagheri

Bibliographic record

VenueIGI Global eBooks · 2009
Typebook-chapter
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsResearch ethicsEthics committeeDeveloping countryPolitical scienceEngineering ethicsTask (project management)Public relationsResource (disambiguation)Ethical issuesPublic administrationEconomic growthEngineeringManagementEconomicsComputer science

Abstract

fetched live from OpenAlex

This chapter elaborates on some of the existing concerns and ethical issues that may arise when biomedical research protocols are proposed or funded by research institutes (private or public) in developed countries but human subjects are recruited from resource-poor countries. Over the last two decades, clinical research conducted by sponsors and researchers from developed countries to be carried out in developing countries has increased dramatically. The article examines the situations in which vulnerable populations in developing countries are likely to be exploited and/or there is no guarantee of any benefit from the research product, if proven successful, to the local community. By examining the structure and functions of ethics committees in developing countries, the article focuses on the issues which a local ethics committee should take into account when reviewing externally-sponsored research. In conclusion, by emphasizing capacity building for local research ethics committees, the article suggests that assigning the national ethics committee (if one exists) or an ethics committee specifically charged with the task of reviewing externally-sponsored proposals would bring better results in protecting human subjects as well as ensuring benefit-sharing with the local community.

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)0.021
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.415
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.016
Insufficient payload (model declined to judge)0.0000.001

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 head0.550
GPT teacher head0.584
Teacher spread0.034 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations4
Published2009
Admission routes1
Has abstractyes

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