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Record W4415586878 · doi:10.21083/crrf.v34i1.7781

The Intersection of Mutual Aid and Third Places in Rural Nova Scotia During the COVID-19 Pandemic

2025· article· W4415586878 on OpenAlexaffabout
John Dale, Ryan Colin Gibson

Bibliographic record

VenueProceedings of the Canadian Rural Revitalization Foundation · 2025
Typearticle
Language
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNova scotiaMutual aidPandemicUnit (ring theory)Intersection (aeronautics)Nova (rocket)Relation (database)Social capital

Abstract

fetched live from OpenAlex

This ongoing research project intends to explore three primary items:• What is the relationship between mutual aid and third places in rural Nova Scotia?• How has this relationship changed with the COVID-19 pandemic?• What gaps might answering these questions reveal? And how do these items change the waywe think about social capital and community welfare?Literature outside of Nova Scotia indicates that the majority of mutual aid in the US and Canada is concentrated within the family unit or cultural community, rather than the larger neighbourhood. What do these geographies look like in rural Nova Scotia, and how has the COVID-19 pandemic impacted the established landscape? Considering its relation to public space, are actors withdrawing to their immediate familial supports, whether they want to or not, or is COVID-19encouraging unique methods of community-building and care? Exploring these themes might help provide some insight into identifying policy gaps, challenges and opportunities to support capacity-development for explicit mutual aid projects, as well as providing a peek into this matter as it relates to pandemic conditions, namely COVID-19.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.301
Teacher spread0.280 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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