Research questions that matter: Engaging Aboriginal youth in the research process
Bibliographic record
Abstract
Within the research literature, there is a well recognized need for descriptive, comprehensive, research that identifies Aboriginal peoples' determinants and barriers to physical activity (Young & Katzmarzyk, 2007). In an effort to address this gap, and to optimize on an opportunity to advance the current physical activity literature, it is critical to ensure that appropriate research questions are being addressed. Thus, Aboriginal peoples need to be involved in the development of research questions. The purpose of this development project was to engage Aboriginal youth and key stakeholders in community consultations to identify a specific research question that is relevant and respectful in addressing the physical activity of Aboriginal youth. Six community consultations, ranging in size from 10-15 Aboriginal youth and stakeholders, took place over three months. Consultations were recorded and transcribed verbatim, and a thematic analysis was conducted. The primary themes that were described by participants will be discussed, and the finalized research question will be presented. As well, the lessons learned from engaging in community consultations for the purpose of developing a relevant physical activity research question will be discussed. Acknowledgments: Thank you to the participants for actively engaging in the research process and to SSHRC for funding this research.
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 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 | 0.154 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.016 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".