Exploring the Potential of Social Media Platforms as Data Collection Methods for Accessing and Understanding Experiences of Youth with Disabilities: A Narrative Review
Bibliographic record
Abstract
Purpose: Social media (SM) is a critical component of youth culture, and may provide a useful platform for exploring young people’s authentic voices. This narrative review considers how researchers are exploring the experiences of youth with disabilities using SM. Methods: Five health and social science databases were searched using terms related to ‘social media’ and ‘data collection’. Articles were reviewed for relevancy. Narrative analysis was undertaken. Results: Searches returned 1524 results, of which 15 articles were included. SM-based data collection methods fell into three categories: 1) observational; 2) interactive; and 3) combined online/offline, each offering unique advantages to data collection. Literature suggests that SM can be used to effectively explore self-care, coping and social experiences of youth with health conditions, however youth with disabilities were notably absent from all three categories. Conclusion: As a prominent component of youth culture, researchers have turned to SM-based data collection methods to understand youths’ real-world experiences. It is imperative, however, that the voices of youth with varied abilities and backgrounds be included in the conversation.
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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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".