Revitalización urbana y calidad de vida en el sector central de las ciudades de Montreal y México
Bibliographic record
Abstract
El abandono y consiguiente despoblamiento del sector central asociado a una desenfrenada expansión y poblamiento de los sectores periféricos de muchas de las grandes ciudades norteamericanas como Montreal y México, es un problema de actualidad muy difícil de resolver. Encontrar las causas que provocan dicho proceso se convierte en una necesidad crítica para mejorar el diseño de políticas urbanas que promuevan la re-utilización del espacio central, desalentando la utilización de los periféricos.En función de diversos programas urbanos tanto Canadienses como Mexicanos implementados al momento en el sector central de las dos ciudades mencionadas, ésta tesis se apoya en dos estudios de campo y los correspondientes análisis estadísticos de correlación y de regresión entre otros, para explicar el estado que el continuo revitalización urbana-calidad de vida-calidad del lugar guarda en el sector central de los casos de estudio desde la propia perspectiva de sus residentes.Los resultados informan que en revitalización urbana, los residentes Canadienses favorecen más a los atributos de calidad del lugar mientras que sus homólogos Mexicanos favorecen más a los de calidad de vida.ABSTRACT: The neglect and further depopulation in many of the large North American cities’ inner-cores such as Montreal and Mexico coupled with sprawl and repopulation in their peripheral areas is very much a today’s problem difficult to solve. Finding out the causes that incite that process becomes a critical need to improve the design of urban policies that promote the re-utilization of the central space, to discourage the equivalent in the peripherals one.Taking into account several urban Canadian and Mexican programs already implemented on those cities’ inner cores, this thesis makes use of two field surveys and the corresponding correlation and regression statistical analyses among others, to explain the current urban revitalization > quality of life > quality of place situation in the already mentioned inner-core of both study cases from their residents’ point of view.Results in terms of urban revitalization indicate that Canadian residents favour more the quality of place attributes meantime Mexican residents favour more the quality of life attributes.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".