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Record W2620760522 · doi:10.1177/1049732317712489

“I Have Strong Hopes for the Future”: Time Orientations and Resilience Among Canadian Indigenous Youth

2017· article· en· W2620760522 on OpenAlexaffabout
Andrew R. Hatala, Tamara Pearl, Kelley Bird‐Naytowhow, Andrew Judge, Erynne Sjoblom, Linda Liebenberg

Bibliographic record

VenueQualitative Health Research · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsDalhousie UniversityFirst Nations University of CanadaUniversity of SaskatchewanWestern UniversityUniversity of Manitoba
Fundersnot available
KeywordsIndigenousResilience (materials science)PsychologyPsychological resiliencePolitical scienceSociologyGerontologySocial psychologyMedicine

Abstract

fetched live from OpenAlex

In this article, we demonstrate how concepts of time and the future inform processes of resilience among Indigenous adolescents within an urban Canadian context. This study employed a modified grounded theory methodology by conducting 38 qualitative interviews with 28 Indigenous youth (ages 15-25) over the course of 1 year. The analysis revealed complex processes of and navigations between moments of distress and strategies for resilience. The distressing contexts in which Indigenous youth often find themselves can impact the development of their concepts of time and limit their abilities to conceptualize a future. A future time orientation (FTO) emerged as central to processes of resilience and was supported by (a) nurturing a sense of belonging, (b) developing self-mastery, and

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)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0120.009
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
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 head0.450
GPT teacher head0.617
Teacher spread0.167 · 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

Citations51
Published2017
Admission routes2
Has abstractyes

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