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Record W6983605590

Nature, winter and architecture: a winter community on Manitoulin Island designed to provide benefits to the residents, landscape and island during the winter months

2021· dissertation· en· W6983605590 on OpenAlexaboutno aff

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2021
Typedissertation
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsTourismPopulationVariety (cybernetics)Local communityClosing (real estate)
DOInot available

Abstract

fetched live from OpenAlex

This thesis proposes the design of a community that focuses on architecture, and winter living
\non the landscapes of Manitoulin Island, Ontario. The proposed community aims to provide solutions
\nin direct response to the social and living challenges brought by the colder months, experienced
\nby permanent residents, summer residents, and tourists. In addition to providing benefits to the
\nusers, the solutions to these issues also aim to increase winter population and revitalize the Island
\nduring winter months. The question of my thesis is, How can the design of a community aid in
\nimproving the social and living challenges faced by residents and tourists, and revitalize
\nManitoulin Island during the winter months?
\nManitoulin Island’s landscapes are ideal for camping, boating, hiking, hunting, snowmobiling,
\nand other outdoor activities. Although the Island has a very successful tourism industry, it is still
\nsubject to issues experienced by residents and tourists during the colder months. Minimal focus is
\nput on winter living, resulting in a drastic decrease in winter population in contrast to the increase
\nseen during the summer. This decrease is due to the closing of local businesses and campgrounds
\nthat are not designed for year-round use in Northern Ontario, thus deterring people from visiting
\nduring these colder months.
\nThe primary programs that drive the proposed community are a network of trails, marina,
\nbeach, residential housing, a market centre, and a variety of social spaces and activities. These
\nprograms center around connecting with nature, living with the landscape, and creating a strong
\nsocial environment among residents and visitors. Most importantly, these programs are designed
\nto provide the visitors and residents of the community with activities and opportunities for a healthy
\nlifestyle during the winter months. The design of the community focuses on the individual human scale,
\nmiddle scale (larger gatherings of people), and the community scale, as well as the environmental
\nscale.
\nResearch presents an understanding of how people live with the landscape, ecosystem
\nservices, biophilic design, human needs, landscape needs, and how these are met, as well as how
\nboth humans and nature can coexist and benefit from each other. In designing the community,
\nattention is focused on how it is placed in the landscape, public and private space, circulation,
\nand how the design of the site influences the use of the community. A community that is able
\nto successfully implement these characteristics is campgrounds. Campgrounds are studied to
\ndetermine the patterns, physical layouts, social dynamics, demographics, and statistics that make
\nit successful. On Manitoulin Island, campgrounds have a diverse and strong social network while
\nencouraging respect for the environment; elements that this community hopes to achieve.
\n\t Manitoulin Island would significantly benefit from a residential community nestled within its
\nwinter landscape, designed to respectfully interact with the landscape during all seasons; offering
\nresidents year-round access and use to a place that provides lifelong social, ecological, and
\narchitectural benefits. A desired benefit of this community design proposal is for it to be highly
\nadaptable for locations throughout Northern Ontario and in other cold climates.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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
Published2021
Admission routes1
Has abstractyes

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