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Record W6997310625

The unseen Wilderness - reconnecting humans with nature in interior spaces

2024· dissertation· en· W6997310625 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2024
Typedissertation
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsWildnessEmbodied cognitionWildernessNatural (archaeology)PracticumArchitectureOutdoor educationLandscape architectureSublimePosthumanismEthnography
DOInot available

Abstract

fetched live from OpenAlex

In response to the challenges related to implementing natural objects in architectural designs, this practicum proposes recreating the Wildness (Cronon 1996), which means the experience of nature, as an alternative way to connect humans with nature in the built environment. Reviewing Wildness through the lenses of Martin Heidegger’s Being-in-the-World and Maurice Merleau-Ponty’s Phenomenology, nature is not perceived by preserving and observing natural objects like plants and water but by the embodied experience. Edmund Burke’s Sublime and Stephen Kellert’s Biophilia theories are examined through the idea of Wildness to identify common spatial characteristics of nature. Adopting Peter Zumthor and Juhani Pallasmaa’s phenomenological design approach that recreates the embodied experience of a place through architectural elements that constitute a building, this practicum tests identifying the Wildness in different natural settings with specific senses, feelings, and spatial conditions to inform the designs of materials, light, scale, movement, and details in three hypothetical interior spaces. The investigation also considers how the design elements may evoke the memory and imagination of nature to deepen the embodied experience and connect humans with nature.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.205
Teacher spread0.196 · 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 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
Published2024
Admission routes1
Has abstractyes

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