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Record W2059238933 · doi:10.1515/ijamh.2007.19.2.117

Ethical issues surrounding studies with vulnerable populations: A case study of South African street children

2007· article· en· W2059238933 on OpenAlexaff
Magdalena S. Richter, Jean Ν Groft, Lizelle Prinsloo

Bibliographic record

VenueInternational Journal of Adolescent Medicine and Health · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBeneficenceVoluntarinessAutonomyGuardianInformed consentEconomic JusticeResearch ethicsPsychologyMedicineCriminologyPolitical scienceLawPsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

UNLABELLED: Researchers who investigate social and economic determinants of health often interact with vulnerable and marginalized populations. Great care must be taken to conduct research studies involving vulnerable persons in a manner consistent with accepted ethical principles in order to protect participants from exploitation, to build capacity, and to promote wellbeing. Children form a particularly vulnerable group, especially those who do not enjoy the protection of parents or guardians. METHODS: A research project which studied South African Sunnyside's street children was used as a case study to illustrate ethical issues surrounding research with vulnerable populations. DISCUSSION: The participants in the case study lacked the age of majority and were without any legal guardian. The researchers experienced considerable difficulty in obtaining ethical approval to conduct the study. The street children, at first, were not allowed to give informed consent for the study because of their minor age. Ethical principles of autonomy, disclosure, competence and understanding, consent and voluntariness, beneficence and non-maleficence, and justice are described and applied to this case study involving street children in a South African neighbourhood. It is suggested that by working within an ethical framework, the safety of research participants will be assured and the quality of the research will be enhanced.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.236
GPT teacher head0.547
Teacher spread0.311 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations47
Published2007
Admission routes1
Has abstractyes

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