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Record W4416899765 · doi:10.1515/9780228024835

SCAR/CITY

2025· book· W4416899765 on OpenAlexaboutno aff
Daniela Elza

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2025
Typebook
Language
FieldSocial Sciences
TopicPublic Spaces through Art
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryContext (archaeology)NegotiationSpace (punctuation)LeaseUrban space

Abstract

fetched live from OpenAlex

When the trees came down no one knew how / to interpret the light. homeless / it bounces off glass surfaces / pierces the wandering eye– These poems walk streets and take snapshots of the impact financialization of our homes has on our sense of community and belonging. Meandering through physical and philosophical materials – cement, memory, water, narrative, history, sand, light, concrete, and others’ voices – Daniela Elza documents this urgent moment. The reader winds through fragments amidst urban fragmentation. A sequence of triptych poems hearkens to silos, skyscrapers, and streets. Readers here have a choice: they can read across the page or down. She channels Syrian architect Marwa Al-Sabouni, who says, “The fabric of our cities is reflected in the fabric of our souls.” SCAR/CITY emerges from the Vancouver context to take on global issues of predatory finance and a market that mines homes for profit. It steps outside of binary conversations in favour of poetic reflection and interrogates a system that results in perceptible depravity and scarcity, which leaves us homeless, metaphorically and literally. French philosopher Gaston Bachelard says, “The space we love is unwilling to remain permanently enclosed … Space calls for action, and before action, the imagination is at work.” Amidst negotiations and advocacy in the fight for security of tenure and lease renewal, SCAR/CITY is a poetic call to action.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0050.003
Scholarly communication0.0000.001
Open science0.0040.004
Research integrity0.0020.002
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 head0.249
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMcGill-Queen's University Press eBooksSame topicPublic Spaces through ArtFrench-language works237,207