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Record W7056177203

Deconstructing the threshold: a new architectural language for the three nations border crossing

2019· dissertation· en· W7056177203 on OpenAlexaboutno aff

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2019
Typedissertation
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsBorder crossingBridge (graph theory)Identity (music)Space (punctuation)Border SecurityArchitecture
DOInot available

Abstract

fetched live from OpenAlex

Deconstructing the Threshold: A New Architectural Language for the Three Nations Border Crossing confronts the philosophical framework of the international border between Canada and the United States. By identifying three fictions, following Peter Eisenman in his essay “The End of the Classical: The End of the Beginning, the End of the End,” the thesis categorizes the language of a border crossing into three fictions: Identity (Meaning), Truth (Threshold) and History (Borders through Time). By understanding these fictions to be the message that Ports of Entry (POE) are designed to convey, how can they be deconstructed, to be read by groups of people who do not acknowledge the border? The study site and location of a building proposal is located at the Seaway International Bridge Crossing spanning between Cornwall, Ontario and Rooseveltown, New York. The site plays an important role in the ideas presented in the thesis as the site is the location of Akwesasne First Nation, unceded Mohawk territory which is bisected by this border, reinforcing the idea of borders as abstract constructs. As borders are not percieved in the same way by everyone this thesis poses the question - how can a threshold become a space that embodies the idea of shared collective difference?

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.042
Scholarly communication0.0150.014
Open science0.0020.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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 designTheoretical or conceptual
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

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