Language of Instruction and Ethnic Disparities in School Success

Abstract

In Quebec’s French-language secondary schools, youth originating from South Asia have the highest dropout rate among all immigrant-origin students, whereas in the English sector, their coethnic peers have a more positive academic profile than third-plus-generation students. Using quantitative data, this paper aims to understand the difference in school performance between these two groups. Firstly, we examine their performance through three indicators: school delay, graduation, and dropout rates. Secondly, we contrast their profile through nine characteristics. Finally, we discuss the influence of each group’s characteristics on graduation. The results reveal that the difference in performance is largely due to the characteristics of the French-sector students. The English-sector students’ success is not significantly related to having English as mother tongue or as language spoken at home.Au Québec, dans les écoles secondaires de langue française, les jeunes d’origine sud-asiatique ont le taux de décrochage le plus élevé parmi les élèves issus de l’immigration, alors que dans le secteur anglais, leurs compatriotes ont un profil académique plus positif que les élèves de troisième génération et plus. En utilisant des données quantitatives, cet article vise à comprendre la différence de performance scolaire entre ces deux groupes. Tout d’abord, nous examinons la performance à travers trois indicateurs : le retard scolaire, l’obtention du diplôme et le taux de décrochage. Nous comparons ensuite le profil de chaque groupe selon neuf caractéristiques. Enfin, nous discutons de l’influence des caractéristiques de chaque groupe sur l’obtention du diplôme. Selon les résultats, la différence de performance est due en grande partie aux caractéristiques des élèves du secteur français. La réussite des élèves au secteur anglais n’a pas été significativement liée au fait d’avoir l’anglais comme langue maternelle ou comme langue d’usage à la maison

Epidemiology of hospitalised traumatic brain injury in the state of New South Wales, Australia: a population‐based study

“…Remoteness was classified according to the Australian Standard Geographical Classification 21 . Statistical comparisons involved the following subgroups: for socioeconomic status, the most disadvantaged (classifications 1–3) versus medium (classifications 4–7) versus least disadvantaged (classifications 8–10); 22 for location, metropolitan (classification 1) versus rural (classifications 2–3) versus remote living location (classification 4–5). Cause of injury was classified as follows using the ICD external cause (E‐Codes): transport accidents, falls, assaults 7 and other mechanisms. Cases with more than one E‐Code were described as multiple mechanism TBI group and regarded as a separate group. Associated factors of TBI risk were ascertained from the diagnosis codes as follows: alcohol consumption, drug use, sports, recreational activities. Severity was assessed using ICD‐code information on post‐traumatic amnesia (PTA) and LoC duration.…”