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Record W4315631238 · doi:10.38140/ijrcs-2023.vol5.01

Exploring Community Resilience towards Rebuilding Community Identity After the Portapique Mass Shooting in Canada

2023· article· en· W4315631238 on OpenAlexaffabout
Megan Netzke, Bettina Callary, Leigh Potvin

Bibliographic record

VenueInterdisciplinary Journal of Rural and Community Studies · 2023
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsLakehead UniversityCape Breton University
Fundersnot available
KeywordsIdentity (music)Community resiliencePsychological resilienceThematic analysisResilience (materials science)Public relationsSociologyAutoethnographyCommunity engagementNova scotiaGrassrootsSense of communityPolitical scienceQualitative researchGender studiesPsychologySocial psychologySocial scienceAestheticsEngineeringLaw

Abstract

fetched live from OpenAlex

This research aims to explore the significance of citizen participation in rebuilding a sense of community identity and facilitating the communal healing process in the aftermath of the public shooting in Portapique, Nova Scotia. We approached this research using autoethnography and completed a thematic analysis of the first author’s journal entries written in the ten months following the public shooting. We generated two higher-order themes- posttraumatic stress responses and factors of resilience. These two themes provided the framework on which to organise the data. The findings indicate the significance citizen participation and event organisation have on a community’s ability to exhibit resilience and the detrimental effects that can occur when support is not community-led. Through the lens of participation in community organising (the Portapique Community Build-Up project), participation was the crucial link to building a sense of community identity.

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)0.015
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0130.000
Scholarly communication0.0000.001
Open science0.0010.007
Research integrity0.0000.012
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 head0.267
GPT teacher head0.459
Teacher spread0.193 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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