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Drawing on data from students, higher education staff and policymakers from six European countries, this article argues that it remains a relatively common assumption that students should be politically engaged. However, while students articulated a strong interest in a wide range of political issues, those working in higher education and influencing higher education policy tended to believe that students were considerably less politically active than their predecessors. Moreover, while staff and policy influencers typically conceived of political engagement in terms of collective action, articulated through common reference to the absence of a 'student movement' or unified student voice, students' narratives tended not to valorise 'student movements' in the same way and many categorised as 'political' action they had taken alone and/or with a small number of other students. Alongside these broad commonalities across Europe, the article also evidences some key differences between nation‐states, institutions and disciplines. In this way, it contributes to the comparative literature on young people's political engagement specifically, as well as wider debates about the ways in which higher education students are understood.

This article examines how higher education (HE) students are conceptualised in Spain, drawing on an analysis of policy and institutional narratives about such students, as well as on the perspectives of university staff and students themselves. More specifically, it will explore an interesting paradox that we encountered in our data: on one hand, marketisation is less firmly established in the HE system of Spain than in many other European countries, and policy and institutional narratives in Spain present the HE system as being relatively unmarketised. On the other hand, the staff and students we interviewed presented the Spanish HE system and the student experience as having been dramatically transformed by marketisation. In analysing this paradox, the article highlights the importance of not viewing countries as coherent educational entities. In addition – while broadly supporting scholarship that has pointed to a growing market orientation of national HE systems across Europe – the article draws attention to how the manner in which the marketisation of HE is experienced on the ground can be very different in different national contexts, and may be mediated by a number of factors, including perceptions about the quality of educational provision and the labour market rewards of a degree; the manner in which the private cost of education (if any) is borne by students and their families; and the extent to which marketisation may have become entrenched and normalised in the HE system of a country.

Part I: Regional cooperation models, processes and obstacles Part II: Domestic politics and its foreign policy implications Part III: Political economy and regional cooperation

The Advancing Data Justice Research and Practice project aims to broaden understanding of the social, historical, cultural, political, and economic forces that contribute to discrimination and inequity in contemporary ecologies of data collection, governance, and use. This is the consultation draft of a guide for policymakers. It provides actionable information for policymakers who wish to implement the principles and priorities of data justice in their policymaking activities. In the first section, we introduce the nascent field of data justice, from its early discussions to more recent proposals to relocate understandings of what data justice means. This section includes an account of the outreach we conducted with stakeholders throughout the world in developing a nuanced and pluralistic conception of data justice and concludes with a description of the six pillars of data justice around which this guidance revolves. Depending on their contexts, potential impacts, and scale, data policymaking activities may be carried out in a way that involves stakeholder engagement. To facilitate this process, the next section provides an explainer of the Stakeholder Engagement Process and the steps it includes—preliminary horizon scanning, policy scoping and stakeholder analysis, positionality reflection, and establishing stakeholder engagement objectives and methods. Finally, the last section presents the guiding questions that will help policymakers address issues of data, digital infrastructures, and affected areas of civic, public, and private life, throughout the policy lifecycle and in accordance with the six pillars of data justice. ; This report was commissioned by the International Centre of Expertise in Montréal in collaboration with GPAI's Data Governance Working Group, and produced by the Alan Turing Institute. The research was supported, in part, by a grant from ESRC (ES/T007354/1), Towards Turing 2.0 under the EPSRC Grant EP/W037211/1, and from the public funds that make the Turing's Public Policy Programme ...

The Advancing Data Justice Research and Practice project aims to broaden understanding of the social, historical, cultural, political, and economic forces that contribute to discrimination and inequity in contemporary ecologies of data collection, governance, and use. This is the consultation draft of a guide for impacted communities. It provides actionable information for communities who wish to implement the principles and priorities of data justice. In the first section, we introduce the nascent field of data justice, from its early discussions to more recent proposals to relocate understandings of what data justice means. This section includes an account of the outreach we conducted with stakeholders throughout the world in developing a nuanced and pluralistic conception of data justice and concludes with a description of the six pillars of data justice around which this guidance revolves. Depending on their contexts, potential impacts, and scale, data activities may be carried out in a way that involves stakeholder engagement. To facilitate this process, the next section provides an explainer of the Stakeholder Engagement Process and the steps it includes—preliminary horizon scanning, policy scoping and stakeholder analysis, positionality reflection, and establishing stakeholder engagement objectives and methods. This section sets out considerations relating to internal community engagement (i.e. engagement within your community) as well as approaches to engaging external stakeholders (i.e. to inform or influence external activities). Additionally, it sets out considerations to be addressed when participating in externally-led engagement processes (e.g. where communities are invited to participate in stakeholder engagement initiated by developers or policy-makers). Finally, the last section presents the guiding questions that will help communities to address issues of data, digital infrastructures, and affected areas of civic, public, and private life, in relation to past, present and future dimensions of ...

For Germany, India is the second most important source of foreign postgraduate students, after China. Student flows from India are contributing significantly to Germany's efforts to internationalise higher education in the country and address labour market skills shortages. Understanding what is driving postgraduate student migration from India to Germany is crucial for further increasing these flows. In India, awareness about Germany as a study destination has been growing in recent years but remains low compared to awareness regarding more traditional study destinations for Indian students, such as the USA, the UK, and
Australia. Indian students heading to Germany are attracted by the low cost of education, courses taught in English, the perceived high quality of education, the availability of paid part-time work opportunities during study, an 18-month post-study visa, and the EU Blue Card scheme, together with the perceived availability of
good jobs. Overall, the cost advantage German universities offer over universities in the USA,
the UK, and Australia is the main draw for most students heading to Germany. Engineering and information technology (IT) courses are the most popular
among Indian students in Germany, with the vast majority of these students enrolled on such courses. Students first encounter the possibility of study in Germany through their social networks or private education consultancies, both of which - along with
social media sites - serve as important conduits of information and support to aspirant student migrants to Germany. Policy Implications: To benefit from rising Indian student flows to Europe, the cost advantage of
German universities must be preserved. Also, students should be given more opportunities to directly interact with representatives of German universities, as education consultancies have limited incentives to recommend study in Germany. The value of embarking on courses other than engineering should be demonstrated.

Indien ist nach China das zweitwichtigste Herkunftsland graduierter Migranten, die in Deutschland studieren. Die Zuwanderung von Studierenden
aus Indien trägt signifikant dazu bei, die Hochschulausbildung in Deutschland wie beabsichtigt zu internationalisieren und dem Fachkräftemangel entgegenzuwirken. Dieser Zustrom indischer Absolventen lässt sich nur
verstärken, wenn wir seine Triebkräfte verstehen. Der Bekanntheitsgrad Deutschlands als Studienland nimmt in Indien seit einigen Jahren zu, ist aber im Vergleich zu den angestammten Zielländern indischer Studierender, z.B. den USA, Großbritannien und Australien, nach wie vor gering. Für Deutschland entscheiden sich indische Studierende wegen niedriger Studiengebühren
und englischsprachiger Studiengänge, weil sie die Bildungsqualität als hoch einschätzen, während des Studiums in Teilzeit arbeiten und nach ihrem Studienabschluss ein 18-monatiges Visum erhalten können, sowie dank der Blauen
Karte EU und der bekanntermaßen günstigen Arbeitsmarktlage. Die Hauptmotivation der meisten Studierenden, nach Deutschland zu kommen, ist jedoch der Kostenvorteil deutscher Universitäten gegenüber den USA, Großbritannien und Australien. Die bei indischen Studierenden in Deutschland beliebtesten Fachrichtungen sind Ingenieurwesen und Informationstechnologie (IT); die überwiegende Mehrheit von ihnen ist in diesen Studiengängen eingeschrieben. Auf die Idee, in Deutschland zu studieren, werden junge Inder durch ihre sozialen
Netzwerke oder private Studienberatungsagenturen gebracht. Letztere sind - neben den sozialen Online-Medien - wichtige Multiplikatoren und unterstützen Studierende, die ein Studium in Deutschland anstreben.
Fazit: Um von der wachsenden Zuwanderung indischer Studierender nach Europa zu profitieren, muss der Kostenvorteil deutscher Universitäten erhalten bleiben.
Da es für Studienberatungsagenturen nur begrenzt attraktiv ist, ein Studium in Deutschland zu empfehlen, sollten Studierenden mehr Möglichkeiten angeboten
werden, direkt mit Vertretern deutscher Universitäten Kontakt aufzunehmen. Es sollte zudem deutlich gemacht werden, dass auch nichttechnische Studiengänge
aussichtsreich sind.

The idea of "data justice" is of recent academic vintage. It has arisen over the past decade in Anglo-European research institutions as an attempt to bring together a critique of the power dynamics that underlie accelerating trends of datafication with a normative commitment to the principles of social justice—a commitment to the achievement of a society that is equitable, fair, and capable of confronting the root causes of injustice.However, despite the seeming novelty of such a data justice pedigree, this joining up of the critique of the power imbalances that have shaped the digital and "big data" revolutions with a commitment to social equity and constructive societal transformation has a deeper historical, and more geographically diverse, provenance. As the stories of the data justice initiatives, activism, and advocacy contained in this volume well evidence, practices of data justice across the globe have, in fact, largely preceded the elaboration and crystallisation of the idea of data justice in contemporary academic discourse. We have organised the stories contained in this repository into two groups. The first group, 'Challenges to Data Justice: Stories of Data Discrimination and Inequity", poses the question: What are the sorts of problems and challenges to which data justice practitioners are responding? This section is intended to orient the reader to the range of empirical problems faced by data justice researchers and practitioners the world over. We have provided examples of data practices that have been criticised as posing risks of moral injury and that have been identified as leading to inequitable or discriminatory outcomes. Case studies include a national ID card that serves as a government payment system in Venezuela, a courier service/digital technology company in Colombia, and a digital registry of 'rights, tenancy, and crops' in India. The second group, 'Transformational Stories of Data Justice: Initiatives, Activism, and Advocacy', poses the questions: What do responses to the range of ...

The Advancing Data Justice Research and Practice project aims to broaden understanding of the social, historical, cultural, political, and economic forces that contribute to discrimination and inequity in contemporary ecologies of data collection, governance, and use. This is the consultation draft of a guide for developers and organisations, which are producing, procuring, or using data-intensive technologies. It provides actionable information for those who wish to implement the principles and priorities of data justice in their data practices and within their data innovation ecosystems. In the first section, we introduce the nascent field of data justice, from its early discussions to more recent proposals to relocate understandings of what data justice means. This section includes an account of the outreach we conducted with stakeholders throughout the world in developing a nuanced and pluralistic conception of data justice and concludes with a description of the six pillars of data justice around which this guidance revolves. Next, to support developers in designing, developing, and deploying responsible and equitable data-intensive and AI/ML systems, we outline the AI/ML project lifecycle through a sociotechnical lens, walking the reader through each phase and noting the ethics and governance considerations that should occur at each step of the way. This portion of the guide is intended to provide a background picture of the different stages of the lifecycle and to show how the data justice pillars can be woven into the stages and their respective sociotechnical considerations. To support the operationalisation data justice throughout the entirety of the AI/ML lifecycle and within data innovation ecosystems, we then present five overarching principles of responsible, equitable, and trustworthy data research and innovation practices, the SAFE-D principles—Safety, Accountability, Fairness, Explainability, and Data Quality, Integrity, Protection, and Privacy. These principles support and underwrite the ...

This resource is divided into two primary sections. The first is an annotated bibliography of works related to our integrated literature review on data justice, and the second is a table of organisations conducting data justice or data justice adjacent work. The annotated bibliography contains works relevant to each theme of the integrated literature review which is an accompanying document to this resource. Within each theme and sub-theme key works as well as summaries are provided to direct the reader to additional readings about the topics. This annotated bibliography is not an exhaustive resource, but rather meant to serve as a starting point for learning more about these topics. The table of organisations contains information about organisations conducting data justice or adjacent data justice work across the globe. To ensure the inclusion of a diverse set of organisations from across the globe and across relevant stakeholder groups, the team adopted a three-pronged approach to the identification of organisations. First, recommendations were taken from our existing advisory board members whose expertise on data justice within their regions of operation allowed them to identify organisations which might have been missed. Second, existing networks were examined to identify small organisations working at the intersection of datafication and social justice. This included the Association of Progressive Communications whose aim is 'empowering and supporting people working for peace, human rights, development and protection of the environment, through the strategic use of information and technologies and Privacy International who aim 'to protect democracy, defend people's dignity, and demand accountability from institutions who breach public trust'. Third, through active research and cascading search, additional organisations were identified based on prior work on datafication and social justice, previous experience of stakeholder engagement, and strong networks among relevant stakeholder groups. The table serves ...