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Record W4251567366 · doi:10.32920/ryerson.14644119.v1

Strategies to animate Toronto's transitional post-industrial waterfront

2021· preprint· en· W4251567366 on OpenAlex
Erin Tito

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

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicLandscape and Cultural Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAnimationRedevelopmentSpace (punctuation)Ephemeral keyPort (circuit theory)Public spaceArchitectural engineeringCivil engineeringComputer scienceGeographyEngineeringComputer graphics (images)

Abstract

fetched live from OpenAlex

Post-industrial waterfronts are spaces in transition. Waterfront land will be redeveloped eventually, and until that time, planners must tum to new approaches for these transitional spaces, with a goal to activate and animate them. Animation strategies can be used in any post-industrial or transitional space, but in waterfronts, they are essential. This paper discusses two case studies. Gas Works Park and Landscape Park Duisburg-Nord are public space projects in which animation techniques have fostered transformation and engagement of the public. Several typologies of post-industrial space illustrate the animation techniques described within the case studies. The paper evaluates these techniques or strategies and applies them to a post-industrial area slated for redevelopment, Toronto's Port Lands. Key Words: post-industrial space, waterfront, animation, loose space, ephemeral landscapes.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.731
Threshold uncertainty score1.000

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0400.000

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 head0.056
GPT teacher head0.242
Teacher spread0.186 · 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

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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