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Record W2477804275 · doi:10.1080/01490400.2016.1203846

“I Like My Peeps”: Diversifying the Net Generation's Digital Leisure

2016· article· en· W2477804275 on OpenAlex
Bronwen L. Valtchanov, Diana C. Parry

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLeisure Sciences · 2016
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNegotiationInteractivityThe InternetSociologyImmigrationSociology of leisureInterpersonal communicationPublic relationsPolitical scienceMultimediaSocial scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The current generation of adolescents is the first to have grown up with the widespread use of the internet as part of their everyday lives; they are the Net Generation. To diversify existing research on this generation's digital practices, this study explored the intersectional experiences of diverse immigrant adolescent girls' digital leisure. Conversational interviews with nine girls revealed that they encountered numerous interpersonal leisure constraints following their immigration to Canada. Within their digital leisure, girls were able to negotiate these constraints through online connections with family and friends back home, Canadian friends, and the global village. These online connections facilitated an expansion of social boundaries and communication with both familiar and broad networks to maintain and develop relationships, pursue interests, share culture, and resist limiting gendered norms with the unparalleled interactivity and sociability of digital leisure.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.055
GPT teacher head0.307
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it