{"id":4676,"date":"2022-09-28T11:00:46","date_gmt":"2022-09-28T09:00:46","guid":{"rendered":"https:\/\/datascience.unifi.it\/?post_type=tribe_events&#038;p=4676"},"modified":"2022-09-28T11:00:46","modified_gmt":"2022-09-28T09:00:46","slug":"disia-seminar-social-background-inequality-in-academic-track-enrolment-how-the-role-of-individual-competencies-teachers-assessments-and-family-decisions-varies-across-italian-provinces","status":"publish","type":"tribe_events","link":"https:\/\/datascience.unifi.it\/index.php\/event\/disia-seminar-social-background-inequality-in-academic-track-enrolment-how-the-role-of-individual-competencies-teachers-assessments-and-family-decisions-varies-across-italian-provinces\/","title":{"rendered":"DISIA Seminar: Social background inequality in academic track enrolment: How the role of individual competencies, teachers\u2019 assessments and family decisions varies across Italian provinces"},"content":{"rendered":"<p><strong>Title<\/strong>: Social background inequality in academic track enrolment: How the role of individual competencies, teachers\u2019 assessments and family decisions varies across Italian provinces<\/p>\n<p><strong>Speaker<\/strong>: <b>Moris Triventi<\/b>\u00a0e\u00a0<b>Emanuele Fedeli<\/b>\u00a0(Universit\u00e0 degli Studi di Trento)<\/p>\n<p><strong>Location:<\/strong> Aula 205 (ex 32) \u2013 DISIA \u2013 Viale Morgagni 59<\/p>\n<p><strong>Abstract:<\/strong> We aim to understand the main sources of social background inequalities in academic track enrolment in Italy and whether their relative importance varies across provinces. Italy is a well-suited case study since it is characterized by low educational attainment rates, high levels of educational inequalities and strong geographical divides in school outcomes. We distinguish between three main general channels by which social inequalities in educational transitions are reproduced, the so-called \u2018primary\u2019, \u2018secondary\u2019, and \u2018tertiary effects\u2019 (Boudon 1974; Esser 2016). They refer respectively to the role of individual competencies, teachers\u2019 assessments and family decisions. We compiled a student population panel dataset from the Invalsi-SNV, following 1,344 million students from five cohorts (2013 \u2013 2017) enrolled in the 8th grade of lower secondary school (untracked) to the 10th grade of upper secondary education (tracked). We use binomial logistic regression models to measure social background inequality and the KHB method to decompose it into the three channels (Karlson et al. 2012). We find that families\u2019 choices, irrespective of students\u2019 abilities and teachers\u2019 evaluations, are the prevalent source of reproduction of inequalities in academic track enrolment, followed by tertiary and then primary effects. Interestingly, we find more geographical heterogeneity in the channels by which educational inequalities are reproduced than in the total inequality by social background, a novel finding in the literature. With this work we complement the cross-national literature and provide new evidence that heterogeneity across contexts does not only refer to the level of social disparities but also to how inequalities are (re)produced.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Title: Social background inequality in academic track enrolment: How the role of individual competencies, teachers\u2019 assessments and family decisions varies across Italian provinces Speaker: Moris Triventi\u00a0e\u00a0Emanuele Fedeli\u00a0(Universit\u00e0 degli Studi di &#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"template":"","meta":{"_monsterinsights_skip_tracking":false,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[35],"class_list":["post-4676","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-seminar","cat_seminar"],"_links":{"self":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/4676","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":1,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/4676\/revisions"}],"predecessor-version":[{"id":4677,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events\/4676\/revisions\/4677"}],"wp:attachment":[{"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/media?parent=4676"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tags?post=4676"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/datascience.unifi.it\/index.php\/wp-json\/wp\/v2\/tribe_events_cat?post=4676"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}