Digital Youth: Privacy, Identity, Play & Sociality in Everyday Spaces
Bibliographic record
Abstract
This ethnographic study investigates the role and meaning of digital culture in the everyday lives of a group of middle-class, urban, young people in Montreal. In this work, I examine how a range of new media and technology are influencing their communication and sociality. Additionally, I consider young people’s changing experience of on and offline spaces, and the ways they have reconstructed notions of public and private identities. \nThe research reflects an interdisciplinary perspective, drawing on ideas from the fields of Sociology, Communications and Education to examine young people’s engagement with digital culture. The study considers how geography, socio-economic class, language, culture and a pervasive anxiety about risk situates and contextualizes their particular experience of technology. \n \nWhile this project reflects on theoretical discussions surrounding young people’s use of technology, it means to highlight their voices. Here, participants share rich accounts of their daily use of technology in school, at home, and on city streets, providing a complex and nuanced interpretation of their own experiences. Their narratives provoke critical questions, such as: How do technologies alter existing social norms? How do young people make important decisions about privacy issues online? How do their digital interactions affect interpersonal relationships in on and offline spaces? \nBoth the stories and the inquiry that emerge from this work contribute a better understanding of what it means for contemporary youth to come of age in an increasingly digital world.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".