MétaCan
Menu
Back to cohort
Record W2955697905 · doi:10.22215/etd/2019-13589

Drowned Landscape: An Architectural Reflection Upon Indigenous Sensibilities in Curve Lake First Nation

2019· dissertation· en· W2955697905 on OpenAlexaboutno aff
Chelsea Jacobs

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicUrban Planning and Landscape Design
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousStorytellingFirst nationGeographyGovernment (linguistics)Reflection (computer programming)Cultural valuesPeninsulaEnvironmental ethicsEnvironmental planningEnvironmental resource managementPolitical scienceSociologyArchaeologySocial scienceNarrativeEcologyArtEnvironmental science

Abstract

fetched live from OpenAlex

This thesis aims to develop an architectural design for the Curve Lake First Nation, which articulates the Anishnaabe sensibilities and encourages the longevity and strengthening of traditional cultural values. Curve Lake First Nation, a peninsula located in Southern Ontario, is home to the Mississauga of the Anishnaabeg nation. After the Federal Government's flooding of Curve Lake for the Trent-Severn Waterway in 1844 and 1908 the community faced devastating impacts to the local ecosystem and the loss of 700 acres of their land. This proposal aims to make use of the drowned land through water treatment, education, and storytelling with the emphasis upon landscape experience, providing the opportunity to facilitate land-based learning practices, encouraging the resurgence of cultural traditions, and outlooks. This thesis asks, how does one create an architectural connection with the land and place whilst respecting the inherent Indigenous sensibilities?

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicUrban Planning and Landscape DesignFrench-language works237,207