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Record W4239152219 · doi:10.32920/ryerson.14656809

Public space: an exhibition of photography and video

2021· preprint· en· W4239152219 on OpenAlexaffabout
Martin Franchi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsExhibitionPublic spaceSpace (punctuation)ZoningPhotographyProperty (philosophy)Private spacePublic relationsVisual artsPublic administrationPolitical scienceSociologyGeographyArchitectural engineeringComputer scienceEngineeringLawArt

Abstract

fetched live from OpenAlex

Public Space is a photographic and video project examining the relationship between the public sphere and private corporations. The project explores various sites throughout Toronto and New York that are on private property but have been built with the intention of allowing the general public to have unrestricted access to these areas. These spaces are referred to as Privately Owned Public Space or “POPS”. The goal of the project is to question and document, through photographic and video practice, these spaces within the urban environment and to challenge others to consider whether these spaces are effective in achieving their intended use and if they are truly accessible to the general public. Loss of the public space is an ongoing issue that faces cities and developers often receive concessions to bylaw zoning requirements in exchange for incorporating POPS. This thesis project is a personal exploration of how these spaces are changing the urban environments of North American cities in the twenty first century.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.039
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0390.005

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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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 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
Published2021
Admission routes2
Has abstractyes

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