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Record W4392972998 · doi:10.26443/mjgh.v11i1.1333

Evidence for employing post-secondary educated youth as research assistants in global health disability research

2022· article· en· W4392972998 on OpenAlexaffabout
Shaun Cleaver, Malambo Lastford Miyandai, Patra Likonge Kapolesai, Lynn Akufuna Nalikenai

Bibliographic record

VenueMcGill Journal of Global Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMcGill University
Fundersnot available
KeywordsParticipatory action researchCitizen journalismMedical educationPublic relationsQualitative researchPerspective (graphical)PsychologyCommunity-based participatory researchSociologyPedagogyPolitical scienceMedicineSocial science

Abstract

fetched live from OpenAlex

This paper presents a participatory qualitative case review of the employment of postsecondary educated assistants in a global health research program. The research program was initiated by a visiting Canadian researcher who was a supervised principal investigator exploring disability in Western Zambia. This research was supported by eight paid Zambian research assistants (RAs), three of whom participated in the case review. The case review was informed by a dialogue in which participants identified and shared their perspectives regarding the effects of the employment of RAs in the program. The perspectives of the RAs about the effects of their employment were identified as two themes: professional skill acquisition and increased quality of life. The perspectives of the visiting researcher regarding the effects of the RA employment were identified as four themes: increased productivity, access to skills, increased integration in the community, and continuity. From the collective perspective of all co-authors, the employment of RAs made this research program more productive, rigorous, and equitable while also creating opportunities for Zambian youth. The co-authors recommend that global health researchers consider employing post-secondary educated RAs and engage in a wider dialogue about expanding and improving this arrangement. These perspectives and recommendations have been generated according to a radical, participatory action, research tradition that should be taken into account as other members of the global health community assess this evidence to inform their own activities.

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)0.068
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0680.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.005
Science and technology studies0.0110.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0010.000

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 head0.460
GPT teacher head0.644
Teacher spread0.184 · 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.

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

Citations0
Published2022
Admission routes2
Has abstractyes

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