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Record W3136175746

SUBURBAN IMMIGRANT SETTLEMENTS IN TORONTO AND TRANSPORTATION IMPLICATIONS

2021· dissertation· en· W3136175746 on OpenAlexaboutno aff
Sm Rafael Harun

Bibliographic record

VenueUWSpace (University of Waterloo) · 2021
Typedissertation
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationHuman settlementGeographyTransport engineeringRegional scienceEngineeringArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Immigrants’ social and economic conditions and lifestyles are strong determinants of their residential and transportation choices. Existing studies that analyze immigrants’ transportation behaviour have predominantly focused on a range of socioeconomic factors, yet, they have not accounted for the impacts that the residential patterns of immigrants may have on transportation outcomes. Understanding the spatial settlement patterns of immigrants is critical for learning their travel patterns. Immigrants substantially differ from non-immigrants in the dynamics of residential and transportation decisions. Also, the choice of commuting modes in immigrant neighbourhoods may vary because of the differences in built environment conditions, access to quality transit, and socioeconomic characteristics of the residents. By investigating the Toronto metropolitan region, this dissertation explores the impacts of immigrants’ spatial settlement patterns on their transportation outcomes through three research articles. It makes theoretical and methodological contributions to the immigrant settlement and transportation literature. \n \nThe first research article evaluates the inter-metropolitan-zone variations in immigrant-transportation relationships. Spatially explicit regression models are developed for the Toronto census metropolitan area (CMA) and its three metropolitan zones (inner city, inner suburb, and outer suburb). They compare and contrast the associations between the immigrant concentration levels in the census tracts (CTs) and commuting modal shares while controlling for socioeconomic and built environment factors. Results of the models show that immigrants register strong association with transit use at the CMA level and in each metropolitan zone, where the level of the association is much stronger in the suburbs compared to the inner city. This article detects disproportional transit reliance among immigrants in many areas, such as in Toronto’s suburbs, that are poorly served by transit, and reflects on the reasons and consequences of the revealed phenomenon. It suggests a demand-driven transit strategy that would involve adjusting services to the higher transit reliance of immigrants. The inter-metropolitan-zone comparison in this article adds a new spatial perspective to the understanding of immigrant-transportation relationships. \n \nThe second research article uses the ethnoburb model to explore the spatial evolution patterns of immigrants by investigating the Chinese and South Asians in the Greater Toronto and Hamilton Area (GTHA). It devises a novel approach to evaluate ethnoburbs in a continuum by classifying them into three distinct categories (Nascent, Mature, and Saturated), which can be considered as different stages of ethnoburb development. The assessment of the spatiotemporal changes of the ethnoburb categories demonstrates that the settlement patterns of the immigrants in the suburbs can take different spatial forms depending on the ethnic group under consideration. The article detects a prevalent tendency among both the Chinese and South Asians to form spatial clusters. It additionally recognizes considerable differences in settlement preferences between the groups through their distinct spatial arrangements. This study methodologically advances the ethnoburb delineation process, and theoretically contributes to ethnoburb and immigrant settlement scholarship by highlighting complexities and uncertainties associated with the spatial evolution of ethnoburbs. The spatial settlement trends for the Chinese and South Asians determined in this research article has contributed towards the identification of settlement locations for the two minority immigrant groups in the third research article. \n \nThe third research article compares transportation outcomes relative to the settlements of immigrant groups. Using a series of regression models, it evaluates differences in commuting patterns between the Chinese and South Asian settlements in the suburbs of Toronto metropolitan region and determines the relative influence of the proximity to quality transit on the choice of commuting modes in those areas while controlling for socioeconomic factors. Results from the models show higher transit dependence in the South Asian settlements compared to that of the Chinese. Findings from the study also suggest a stronger influence of socioeconomic factors and employment locations than quality transit on the transportation and residential choices made by immigrant groups. The article manifests unfavourable circumstances for immigrants to use transit in Toronto suburbs by identifying the dissonance among immigrants’ settlement patterns, their choice of commuting modes, and current urban planning approaches. The study advances immigrant-transportation scholarship by adding the transit quality dimension and highlighting inter-immigrant-group differences in immigrants’ settlement and transportation relationships. It makes methodological contributions as well by introducing a new day-long transit quality index for the Toronto metropolitan region. \n \nAs a whole, this dissertation contributes to the understanding of immigrant-transportation relationships and ethnoburb scholarship by i) delineating ethnoburbs using a novel approach and exploring the complexity in their evolution patterns and immigrant settlements more broadly; ii) assessing the spatial dimension to the immigrant-transportation relationships; iii) examining the relative importance of the proximity to quality transit in transportation outcomes in immigrant settlements; and iv) illustrating the urban planning implications of the immigrant settlement and transportation relationships.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes1
Has abstractyes

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