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Record W4393169185 · doi:10.1080/10464883.2024.2303941

Faithful Infidelities

2024· article· en· W4393169185 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Architectural Education · 2024
Typearticle
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsSociology

Abstract

fetched live from OpenAlex

Toronto’s Chinatown was born out of a form of resistance which paired infidelity to official definitions of Canadian citizenship (who was allowed to belong) with fidelity to its community members (who belonged). Historical representations have often been unfaithful to the Chinatown community, and architectural imagery has often tended to erase it from view entirely. In this essay, the authors explore Linda Zhang’s appropriation of architectural technologies (such as photogrammetry and pointcloud scanning) as a form of antidisplacement resistance to the ongoing and centuries-old erasure(s) of Toronto’s Chinatown. Her project, Chinatown 2050, uses speculative futurist 3D reconstructions and community storytelling to reimagine what Toronto’s Chinatowns might be like in the year 2050. Unfaithful to the present and past “official” demarcations of the neighborhood, it is a form of social organizing and imagination towards a more generative future. In countering technological acts of erasure, Zhang’s work illuminates the broader sociopolitical implications of technological choices and critiques the ways in which history often silences marginalized communities.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.236

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)0.0000.000

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 head0.332
Teacher spread0.323 · 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