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Record W7051923917

Remembering the forgotten shore : sustainable development alternatives for Owls Head, Nova Scotia

2022· dissertation· en· W7051923917 on OpenAlexaboutno aff

Bibliographic record

VenueSkemman · 2022
Typedissertation
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsnot available
Fundersnot available
KeywordsTourismIncentiveSustainable developmentCommunity developmentLocal communitySustainable tourismSustainable communityQuality (philosophy)SubsidyCultural heritageSustainability
DOInot available

Abstract

fetched live from OpenAlex

Rural coastal communities are increasingly challenged to innovate and adapt to changes brought on by external economic, environmental, and sociocultural pressures. As a means of adapting to these changes, this study explored sustainable tourism and innovative community-based development strategies within the contexts of conservation and community \nengagement by focusing on the case of Owls Head, Nova Scotia. Supported by background knowledge from an extensive literature review, 13 semi-structured interviews were conducted. Community assets were evaluated with regards to their potential to contribute to sustainable tourism development in the Owl’s Head region. Analysis resulted in five core \nthemes: (1) Recognizing the Importance of Owls Head to NS, (2) Owls Head & Ecosystem Regeneration, (3) Building Trust through Community Engagement, (4) Building Community Resilience through Tourism, and (5) Localized Economic Development. Based on the results, many stakeholders believe that the accessibility and quality of tourist sites surrounding Owls Head can be improved and protected by creating and updating infrastructure. Additionally, interviewees believed programming initiatives are needed to add value to tourist experiences \nand infrastructure. Policy recommendations to stimulate regenerative development could include renewable energy subsidies, incentives for local business development, designation of protected areas, and/or subsidies and grant funding for local organizations and initiatives. The \nmain lessons learned from this study are that development should: restore trust between community members and outsiders, highly value and utilize local ideas and resources, improve access to and quality of the natural environment, showcase the cultural heritage of the region, and inspire further innovation. Further research is needed to understand the full impacts, effectiveness, and complexities of community-based, community-led infrastructure and program development on Nova Scotia’s Eastern Shore.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.277
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2022
Admission routes1
Has abstractyes

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