Digital Media, Mental Health, and Transformative Learning: Conceptualizing Impacts on Marginalization and Equity
Bibliographic record
Abstract
This article describes the results of a qualitative pilot study, conducted with individuals facing multiple statuses of marginalisation and self-reported barriers to formal education (n = 8). This study emphasises the potential utility of fictional media based on narrative or storytelling pedagogies, and posits that the increasing use of arts-based methodologies and media for knowledge translation can improve agency and access to information. With the objective of understanding how digital media contributes to self-initiated lifelong learning, participant responses with specific relevance to mental health are analysed under a transformative learning framework. Results indicate that digital media 1) often takes on a personal nature, resulting in reflections on experiences of trauma; 2) may present an inequitable distribution of negative impacts to individuals who already face marginalisation; 3) is accessed by participants in search of community, while simultaneously creating notable isolation; 4) is affected by the construction of ideologies around digital media, which potentially undermines its potential as a learning tool. Towards supporting the creation of digital media which successfully reduces inequalities in lifelong learning, 18 design considerations conclude this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".