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Record W4232739489 · doi:10.32920/ryerson.14657382

In my back yard

2021· preprint· en· W4232739489 on OpenAlexaffabout
John Verhaeven

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsToronto Metropolitan UniversityUniversity of Victoria
Fundersnot available
KeywordsYardMountNeighbourhood (mathematics)Context (archaeology)AcreGeographyWork (physics)WildlifeVisual artsSociologyArchaeologyCartographyHistoryArtEngineering

Abstract

fetched live from OpenAlex

<p>In My Back Yard is a documentary film that explores the changing landscape of the Mount Dennis neighbourhood in Toronto. This change is represented by the 54-acre Kodak site that is being transformed into the second largest transportation hub in the Greater Toronto Area. The film employs a series of visual strategies and retells recent observations related to the impact of this massive infrastructure project on the people, the land and the urban wildlife. Local residents, politicians and community leader were consulted. Their interviews are combined with dioramas, archival photographs and time-lapse photography to express the multi-facetted list of community concerns. This support paper attempts to define and analyse these struggles within the context of Leo Marx’s 1964 work The Machine in the Garden: Technology and the Pastoral Ideal in America. This paper proposes that Marx’s concept of the “middle landscape” helps to define the current struggle in Mount Dennis.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.808
Threshold uncertainty score0.989

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0350.000

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 head0.048
GPT teacher head0.237
Teacher spread0.189 · 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 teacher head, not a consensus.

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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