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Record W1992127811 · doi:10.1080/13645579.2013.811921

Using respondent-driven sampling with ‘hard to reach’ marginalised young people: problems with slow recruitment and small network size

2013· article· en· W1992127811 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Social Research Methodology · 2013
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsnot available
FundersUniversity of New South WalesAustralian GovernmentPublic Health Agency of Canada
KeywordsRespondentIncentivePopulationSample (material)Social network (sociolinguistics)PsychologySampling (signal processing)Personal networkSociologySocial psychologyDemographyPolitical scienceSocial scienceSocial mediaEconomicsComputer scienceLaw

Abstract

fetched live from OpenAlex

AbstractThis paper documents an experience of using respondent-driven sampling (RDS) to recruit socially marginalised young people in Sydney, Australia. Respondents were young people aged 16–24 years who were current illicit drug users and who reported at least one feature of social marginalisation (e.g. recent homelessness or juvenile detention). Four seeds initiated the sampling and 61 respondents were recruited until the sampling was closed due to slow progress at week nine. The paper examines: (1) the overall success of RDS and compares this with similar RDS studies; and (2) the sufficiency of network ties among respondents. The analyses suggest that RDS was generally successful in that, despite its small size, the sample achieved adequately long recruitment chains and variables converged to equilibrium. Nevertheless, recruitment was much slower than comparable studies. This could be due to the study population having reduced willingness to participate, a high proportion of respondents who did not fit the selection criteria, and small and disparate networks. Using RDS with marginalised youth may require generous resourcing to allow large incentives to increase willingness, and a lengthy recruitment period. Moreover, the small networks suggest that researchers should start the sampling with a large number of seeds.Keywords: young peoplerespondent-driven samplingdrug useAustralia AcknowledgementsThe author wishes to thank the study participants for sharing their time and personal stories, and the Oasis Youth Support Network for their generous contribution of space and expertise. This study was conducted in collaboration with co-investigators Dr Jeanne Ellard and Professor Carla Treloar. Also, the author thanks Dr Dana Paquette for her expert advice about the RDS aspect of the study and the reviewers of this paper for their helpful and constructive feedback. The co-investigators acknowledge the excellent contribution of the study's Reference Group. The study was funded by a grant from NSW Health. The National Centre in HIV Social Research is supported by a grant from the Australian Government Department of Health and Ageing.

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)0.008
metaresearch head score (Gemma)0.004
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 score0.560
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.639
GPT teacher head0.553
Teacher spread0.085 · 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