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Record W4246765471 · doi:10.22215/etd/2021-14585

Diversions: Journeying Vancouver's Pacific Railyards

2021· dissertation· en· W4246765471 on OpenAlexaboutno aff
Alvin P.L. Kwan

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsConversationVernacularIdentity (music)AestheticsSociologyHistoryMedia studiesArtLiterature

Abstract

fetched live from OpenAlex

With the rise in the housing market, and profitability in new developments, historical architectures in Vancouver have been lost, erased, and replaced. These economically-driven developments are sanctioned by the city's administration. Known as 'Vancouverism' this trend creates in the experience of the urban dweller, a sense of loss in tradition, belonging, and identity. This thesis proposes to challenge these rapidly changing urban concerns, exploring how new living experiences might engage with and adapt to Vancouver as an urban playground. To break this cycle of Vancouver's current urban transformation, we will propose speculative architectural interventions and installations with programs that are conceived through the lens of apertures and ruptures - continuities and playful interruptions. This thesis proposes a recto-verso conversation between fact and fiction to challenge the current condition in Vancouver. It dreams to re-think the urban vernacular in Vancouver by engaging its citizens in a world of livable fantasies.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0310.008
Scholarly communication0.0070.001
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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 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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