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Record W2331415869 · doi:10.1080/01490400.2015.1087896

Recreation, Settlement, and the Welcoming Community: Mapping Community with African-Canadian Youth Newcomers

2016· article· en· W2331415869 on OpenAlexaffabout
Graham Campbell, Troy D. Glover, Edwin Laryea

Bibliographic record

VenueLeisure Sciences · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsBrock UniversityUniversity of Waterloo
FundersFlinders University
KeywordsRecreationThematic analysisContext (archaeology)Settlement (finance)SociologySense of communitySocial capitalPerceptionParticipatory action researchGender studiesPublic relationsQualitative researchPsychologyPolitical scienceGeographySocial science

Abstract

fetched live from OpenAlex

The literature on newcomer settlement concentrates almost exclusively on young children and adults, leaving a sizable gap in research related to adolescents. Accordingly, this research project explored the role of community places in the settlement experiences of adolescent immigrants to Canada from Africa. Data were gathered through a cognitive mapping exercise with youth participants who engaged in a larger research project exploring engagement of traditionally underrepresented groups in community-based planning practices. Through thematic analysis of transcripts, videos, and maps, major themes of home and family, social places, and support networks were identified as important in the context of settlement and the perception of a welcoming community. Issues of safety and exclusion were also raised in participants' stories. These themes introduce the roles of family connections, social capital, and third places in contributing to newcomers' sense of place. Leisure settings are highlighted, in particular, as sites of social learning, language skill development, and social connection.

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)0.003
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0320.007
Scholarly communication0.0060.002
Open science0.0030.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.100
GPT teacher head0.305
Teacher spread0.205 · 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

Citations26
Published2016
Admission routes2
Has abstractyes

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