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Record W2969638984 · doi:10.1002/ajcp.12384

Exploring Community Mobilization in Northern Quebec: Motivators, Challenges, and Resilience in Action

2019· article· en· W2969638984 on OpenAlexafffundabout
Sarah Fraser, Shawn‐Renee Hordyk, Nancy Etok, Caroline Weetaltuk

Bibliographic record

VenueAmerican Journal of Community Psychology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec à MontréalUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsHealth psychologyMobilizationPublic healthResilience (materials science)Action (physics)Psychological resilienceCollective actionPsychologyCommunity mobilizationPolitical scienceSocial psychologyEnvironmental healthSociologyMedicineNursing

Abstract

fetched live from OpenAlex

Nunavimmiut (people of the land) are the Indigenous peoples of the northern peninsula of the province of Quebec. Communities of Nunavik and its regional organizations have been making concerted efforts in implementing community-based strategies to support family wellbeing. These community strategies are grounded in many of the values underpinning community psychology: favoring empowerment-oriented approaches, fostering community capacity, and transforming organizational cultures to allow for new modes of interaction, as well as new policies and practices that are grounded in community and culture. Despite the growing support and expectation for community mobilization, there is still very little research on the processes and challenges to such mobilization. In this study, we explored the unique challenges and facilitators to community endeavors in northern Quebec in order to better understand the complex dynamics and the strengths that Inuit build upon. We first used a focused ethnographic approach in the context of a 5-year community mobilization project in Nunavik. We then conducted 12 individual interviews and two small group interviews with Inuit working on community-based wellbeing-oriented mobilization projects in four additional communities. Results expose how sociogeographical realities and colonialism influence the process of community mobilization. They also highlight the values and motivational factors that lead community members to move beyond these influences.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.173
GPT teacher head0.394
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations29
Published2019
Admission routes3
Has abstractyes

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