International Mobility Technology Research: A Delphi Study to Identify Challenges and Compensatory Strategies
Bibliographic record
Abstract
We sought to identify logistical and ethical challenges to performing wheelchair-related research in low- and middle-income countries and to generate a list of compensatory strategies to address these challenges. Thirteen individuals with experience in the field participated in an online Delphi study. The surveys asked participants to identify research challenges, suggest strategies to address the selected challenges, and critique each other's strategies. Participants identified challenges in the use of research techniques, compensation for participation that does not result coercion, oral and written translation materials, funding for research, collaboration with local professionals, and "respect for persons." Effective international mobility research requires time, cultural sensitivity, collaboration, and careful planning. An understanding of these requirements can allow researchers to anticipate and compensate for common pitfalls of their work, thus making the research more productive and beneficial to subjects. Future research is required to verify the general effectiveness of compensatory strategies.
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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 | 0.069 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".