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Rural Resiliency through Heritage Conservation Planning: Research Proposal Presentation

2020· article· en· W4408470948 on OpenAlexaffvenueabout
Sampoorna Bhattacharya

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPresentation (obstetrics)Environmental planningCultural heritageEnvironmental resource managementGeographyArchaeologyEnvironmental scienceMedicine

Abstract

fetched live from OpenAlex

Globally, rural regions face a myriad of challenges such as out-migration, service deficits, and degrading infrastructure. Efforts to combat these obstacles through rapid modernization and development have altered and diminished the cultural and natural heritage characteristics of many communities and regions. Preserving and investing in cultural and natural heritage efforts such as tourism, generational education, and incorporation of indigenous knowledge can foster community pride, civic engagement and improve local sustainability and long-term resiliency. This presentation of my M.Sc research proposal will highlight the research goal and objectives, research methods, case study characteristics, and anticipated outputs. The presentation will conclude with the potential utility of this research on Ontario’s rural communities.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.228
GPT teacher head0.363
Teacher spread0.134 · 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 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
Published2020
Admission routes3
Has abstractyes

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