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Record W1593770955 · doi:10.29173/cjs891

Cultural Centrality and Information and Communication Technology among Canadian Youth

2008· article· en· W1593770955 on OpenAlexaffvenueabout
Victor Thiessen, Dianne Looker

Bibliographic record

VenueThe Canadian Journal of Sociology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsMount Saint Vincent UniversityDalhousie University
Fundersnot available
KeywordsCentralityInformation and Communications TechnologySociologyCohortSurvey data collectionGender studiesPublic relationsPolitical science

Abstract

fetched live from OpenAlex

This paper examines the positions of First Nations, Inuit and Métis (FNIM) peoples and visible minorities as distances from the cultural “centre” of White European culture. It then assesses the relation of information and communication technology (ICT) to these locations among Canadian youth using three data sets: the 2001 Aboriginal Peoples Survey, the 2000 Youth in Transition Survey (older cohort) and its 2002 follow–up, and a 2004/2005 survey collected by the authors. Findings indicate that the idea of cultural centrality is useful in locating FNIM groups and visible minorities vis-à-vis the cultural centre and each other and highlighting the stratified heterogeneity of these groups. Access to, use of, and development of ICT skills tend to mirror the relative positions of these groups in terms of cultural centrality. Further, youth who retain close ties with traditional culture are less unlikely to develop facility with ICT.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0090.003
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.073
GPT teacher head0.340
Teacher spread0.268 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2008
Admission routes3
Has abstractyes

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