Travel behaviour of Asian & European immigrants in the Greater Toronto and Hamilton area
Notice bibliographique
Résumé
Without a better understanding of travel behaviour by diverse immigrant groups, the nuances of immigrant mobility needs may go unmet. Statutory transportation planning requirements focus on mobility “needs”. But social understandings of what travel is “needed” for daily life changes over time varies between different population groups. In many major immigrant settlement areas, immigration has become the primary, if not sole, reason for population growth (Thomas, 2013). Evidence continues to emerge indicating that immigrants use non-auto modes significantly more than non-immigrants but slowly assimilate in becoming more auto-oriented (Chatman, 2013). Likewise, mobility differences between ethnic groups persist (Hu et al., 2020). In the absence of an understanding of the travel behaviour of specific immigrant groups and changes over time, there is a distinct possibility for a significant disconnect between understandings of what transportation services are provided and what services are needed (Blumenberg, 2009; Chatman & Klein, 2009). Towards bridging this gap, this study explores auto ownership and daily vehicle travel among self-identified immigrants and non-immigrants of either self-identified Asian or European descent in the Greater Toronto and Hamilton area. Using data from a 2018 travel survey of residents of the Greater Toronto and Hamilton Area, this study explores travel behaviour in relation to immigrant status and the length of residence in Canada and several mobility measures, including vehicle travel and auto ownership. This study begins by using the survey data to present descriptive statistics related to differences between immigrant groups, based on length of residence in Canada and based on auto ownership and vehicle-kilometers traveled (VKT). Next, inferential models were estimated to formally test the links between travel behaviour outcomes and immigrant status. Logistic regression models of household vehicle ownership were estimated before Tobit regression models of daily VKT were estimated. Descriptive study findings support the expectation of significant differences between immigrant status (based on length of stay) and self-identified ethnicity (Asian or European) and both vehicle ownership and VKT. However, inferential models show a more complex story. Models of household vehicle ownership (yes/no) indicate that being a recent immigrant to Canada is associated with lower vehicle ownership rates, but that effects attenuate rapidly – implying rapid assimilation. Tobit models from this study of daily VKT suggest that these lower rates of auto ownership translate weakly into VKT reductions. Evidence is suggestive of a VKT rebound among Asian populations – wherein some immigrants exceed VKT expectations of non-immigrant groups. These findings beg to question why Asian immigrants use their vehicles so intensely and how mobility gaps are overcome so quickly. Key Words Asian immigrants, European immigrants, travel behaviour, assimilation, Toronto, Hamilton
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».