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Record W2650469819 · doi:10.7202/1040145ar

Going Off, Growing Strong: A program to enhance individual youth and community resilience in the face of change in Nain, Nunatsiavut

2017· article· en· W2650469819 on OpenAlexafffundvenueabout
Rachel Hirsch, Chris Furgal, Christina Hackett, Tom Sheldon, Trevor Bell, Dorothy Angnatok, Katie Winters, Carla Pamak

Bibliographic record

VenueÉtudes/Inuit/Studies · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsGovernment of NunavutMemorial University of NewfoundlandInuit Circumpolar CouncilMcMaster UniversityTrent UniversityBrock University
FundersTrent UniversityStrong
KeywordsPsychological resilienceIndigenousContext (archaeology)MentorshipConceptual frameworkPositive Youth DevelopmentFace (sociological concept)Process (computing)Public relationsResilience (materials science)Adaptive capacitySociologyPolitical sciencePsychologyClimate changeEcologyGeographySocial psychologySocial scienceComputer science

Abstract

fetched live from OpenAlex

Dispossession from social and ecological support systems is a major concern for many Indigenous communities. In response to community health challenges in these settings a number of initiatives such as youth mentorship programs have shown some value in enhancing adaptive capacity. The pilot Going Off, Growing Strong program provides opportunities for at-risk youth to engage in community- and land-based activities and build relationships with positive adult role models in Nain, Nunatsiavut (Labrador, Canada). This paper offers an interpretive description drawing from autobiographical accounts of the development of this innovative program. A collaboratively developed conceptual framework, based on the literature, is used to present and explain program operator’s experiences and rationale for program development. The emergent goals of Going Off, Growing Strong are to strengthen individual youth and collective community resilience through intergenerational exchange of land, social, and cultural skills and knowledge by drawing on social supports, such as a community freezer and experienced harvesters. We found that the process of collaborating over time with multiple stakeholders in creating this conceptual framework was an important one for solidifying the goals of Going Off, Growing Strong and creating context-specific, meaningful evaluation outcomes to enable future measurement of impacts on the community.

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 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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.251
GPT teacher head0.488
Teacher spread0.238 · 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 teacher head, not a consensus.

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

Citations20
Published2017
Admission routes4
Has abstractyes

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