Isabella Sulis, Barbara Barbieri, Luisa Salaris, Gabriella Melis, Mariano Porcu
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引用次数: 0
摘要
目的 本文旨在评估意大利大学生流动性中的性别偏见,并对学习领域进行控制。它使用了意大利国家学生档案(Anagrafe Nazionale degli Studenti - ANS)中关于 2017 学年入学的新生群体的数据。宏观地区比较在以下地区展开:设计/方法/途径首先在国家层面进行分析,其次重点关注宏观地理区域。因此,从性别角度对大学流动性选择进行了调查,并以针对 2017 年入学的未来一年级大学生群体收集的其他理论相关特征为条件。作者在多层次框架内通过回归设置(Logit 模型)分析了数据,该框架考虑了第一层次的学生和第二层次的学习领域。在选择学习领域的条件下,通过引入随机截距来考虑学生在学习领域中的聚类,以及引入随机斜率来考虑性别效应在学习领域中的差异,从而捕捉到成为流动者倾向的性别差异。研究结果研究结果表明,意大利的大学生流动性导致了性别偏见的证据。作者使用多层次随机斜率方法发现了这一现象,该方法允许作者共同估算每个学习领域内的性别斜率参数。此外,作者还利用回归设置控制了不同学生在地理、教育和社会人口特征方面的异质性。与之前的实证研究结果一致,作者的数据强调了大学生从南部向意大利中北部流动的相关性,以及与来自南部和岛屿的男生相比,女生流动性较低的情况。因此,通过调查学生对高等教育的选择,作者可以揭示家庭教育战略中是否存在性别偏见,以增加学生的资产,为未来的工作机会打下基础。
Gender bias in university student mobility: a cohort analysis in Italy
Purpose
This paper aims to assess gender bias in Italian university student mobility controlling for the field of study. It uses data from the Italian National Student Archive (Anagrafe Nazionale degli Studenti – ANS) for the cohort of freshmen enrolled in the 2017 academic year. The macro-regional comparison unfolds across the following areas: North and Centre, Southern Italy and main Islands (Sicily and Sardinia).
Design/methodology/approach
The analysis is firstly carried out at the national level, and secondly, it focusses on macro-geographical areas. University mobility choices are thus investigated from a gender perspective, conditioning upon other theoretically relevant characteristics collected for the prospective first-year university student population enrolled in 2017. The authors analyse data in a regression setting (logit models) within the multilevel framework, which considers students at level 1 and the field of study at level 2. Gender differences in the propensity to be a mover – conditional upon the choice of the field of study – were captured by introducing random intercepts to account for clustering of students in fields of study and random slopes to allow the gender effect to differ among them.
Findings
Findings show that university student mobility in Italy leads evidence of gender bias. This has been detected using a multilevel random slope approach that allowed the authors to jointly estimate a slope parameter for gender within each field of study. Moreover, using a regression setting allowed the authors to control for heterogeneity in geographical, educational and socio-demographic characteristics across students. In line with previous empirical findings, the authors' data highlight the presence of a relevant mobility flow of university students from the South toward the North-Centre of Italy and lower mobility of female students compared to male students from the South and Islands.
Originality/value
To the best of the authors' knowledge, there are no studies in Italy, which investigate if families' investment in higher education in terms of selection of no-local universities are affected by gender bias and if geographical differences in this behaviour between macro-areas are in place. Thus, investigating students' choices in tertiary education allows the authors to shed light on the presence of gender bias in families' education strategies addressed to increase the endowment of students' assets for future job opportunities.
期刊介绍:
■Employee welfare ■Human aspects during the introduction of technology ■Human resource recruitment, retention and development ■National and international aspects of HR planning ■Objectives of human resource planning and forecasting requirements ■The working environment