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Record W7079825054 · doi:10.26108/p9sj-4f13

Navigating the tides of change: community futures planning in Scots Bay, Nova Scotia

2023· other· en· W7079825054 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2023
Typeother
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsScotsNova scotiaParticipatory action researchGeneral partnershipParticipatory planningCommunity developmentEstateGovernment (linguistics)Rural settlementCitizen journalism

Abstract

fetched live from OpenAlex

As rural coastal communities in Nova Scotia, Canada experience a downturn in resource-based industries, community-led development initiatives may lead to revitalization. Scots Bay, Nova Scotia is a small community located at the end of a provincial highway on the Bay of Fundy and home to approximately 200 full time residents and two busy Provincial Parks. The research uncovered that tensions have recently arisen in the community for a variety of reasons and by embarking on a participatory action research project with the residents of this close-knit coastal community, sources of this unease were uncovered. Tens of thousands of tourists bring more garbage and speeding traffic but very little economic benefits. Private development proposals demand time and energy from community members but provide no tangible, enforceable positive impacts. Skyrocketing real estate prices may benefit individuals but threaten the community’s long-held social cohesion with new residents and/or absentee owners. These tensions, combined with an aging population, a lack of rural services, and a sense of political disempowerment, make resident unease palpable. However, by uniquely using the two systems-based community development frameworks of Community Capitals and Three Horizons in conjunction, the project was able to identify how connections to this place and each other ground this community’s residents and find the strengths and assets to build future plans upon. Project participants were able to share concerns and preferences about the future and brainstorm potential solutions. With this information a futures-based Community Action Plan can be created which can help this rural coastal community chart a course on the tides of change. The futures-based process may also prove useful to other rural coastal communities that would like to create their own community-led development initiatives.KEYWORDS<br>Rural Community Development, Coastal Communities, Futures Planning, Community Capitals, Three Horizons, Community Action Planning, Rural Resiliency, Community-Led Development

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
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 head0.086
GPT teacher head0.325
Teacher spread0.239 · 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 designNot applicable
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 routes1
Has abstractyes

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