‘MYBus’: Young People's Mobile Health, Wellbeing and Digital Inclusion
Bibliographic record
Abstract
As part of an ethnographic study researching the role of information and communication technology use in mediating young people’s social inclusion in an outer urban growth area of Melbourne, Australia, this paper reports on a case study of a community mobile youth centre, named MYBus. The MYBus is a converted passenger coach that operates as a mobile youth centre for young people aged 12-25. It aims to provide young people with up-to-date youth-specific information and resources, especially access to health and wellbeing information and services. The bus has been fitted with laptop computers, Internet access, Wii games, D.J. console and other gaming devices to support this engagement. This paper examines how the aggregation of digital media on MYBus not only has direct healthcare benefits, but also enables a broader approach to young people’s wellbeing by providing resources for digital access and participation. In particular, the mobilisation of these technologies operates to redress geographic and socioeconomic inequities for young people living on the urban fringe. We discuss this digital inclusion through research findings related to young people’s digital access, mediation, and mobility in the use of the MYBus technologies. This empirical work is situated theoretically by connecting this mobile digital inclusion with literature on young people’s social capital, to develop the concept of children’s e-mobility capital.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".