Evidence for employing post-secondary educated youth as research assistants in global health disability research
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.143 | 0.143 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".