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Record W602224832

The machine in the garden

2009· dissertation· en· W602224832 on OpenAlexaboutno aff
Andrew Gibson

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2009
Typedissertation
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsTranquillityRural areaOpposition (politics)EngineeringGeographyPolitical sciencePsychologyPoliticsLaw
DOInot available

Abstract

fetched live from OpenAlex

In this study the current conflict over traffic on the Island of Montreal is found to originate in the tension between a belief in nature as an ideal home environment and a belief in technology as an ideal means to resolve social problems. These ideals emerge in the nineteenth century industrial city in response to anxieties over urban life felt by the upper classes. Concerns over health, safety and propriety led to the acceptance of moral instructions that normalized the countryside as the location for family life and generated support for unprecedented investments and developments in transportation technologies to allow people live on the urban fringe. These factors have lead to a situation where a large proportion of society reside in a thickly populated countryside and have adopted mass automobile usage. Current concerns over health, safety and the environment pose challenges to this lifestyle. Conflicts over vehicular access to central neighbourhood streets, the opposition to urban highways, and the drafting of the Montreal Transportation Plan (2007-8) all indicate support for a reduction in automotive traffic and the development of a natural urban environment. This support is indicative of a value system that recognizes tranquillity as a natural attribute of home life. Reducing traffic and producing tranquillity are linked to earlier moral instructions and direct the re-invention of the city and society's continued expansion into the countryside

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.001
Scholarly communication0.0010.000
Open science0.0030.000
Research integrity0.0000.002
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 head0.030
GPT teacher head0.336
Teacher spread0.306 · 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
GenreEmpirical

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
Published2009
Admission routes1
Has abstractyes

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