Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.061 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".