Suchergebnisse

Hat der vielkritisierte deutsche Bildungsföderalismus auch positive Seiten und wirkt, wie die Föderalismustheorie annimmt, als Labor für die Entwicklung und Diffusion von Policy-Innovationen? Diese Frage wird anhand des Hochschulzugangs für beruflich Qualifizierte ohne Abitur untersucht. Die entsprechenden Regelungen waren lange Zeit Sinnbild der föderalen Uneinheitlichkeit, zeigen seit Mitte der 2000er-Jahre jedoch eine überraschende Konvergenz.Auf Grundlage einer Analyse mit standardisierten Daten sowie durch Prozessanalysen von politischen Entscheidungsprozessen zeigt sich, dass unter den Ländern durchaus erfolgreich erprobte Policy-Innovationen diffundieren und die Kultusministerkonferenz (KMK) die Diffusion fördert. Dennoch wird das produktive Potenzial des Bildungsföderalismus nur teilweise ausgeschöpft: Regionale Besonderheiten waren nicht der Ursprung der Policy-Innovation, und Harmonisierung stellte für die politischen Akteure kein treibendes Motiv dar.

Der Einsatz des Milliardensegens ist nicht geregelt - dass die Mittel den bedürftigsten Einrichtungen zukommen, darf bezweifelt werden. Die Ziele des Bildungsgipfels, etwa die Zahl der Schulabbrecher bis 2015 zu halbieren, wären nur durch langfristige Investitionen zu erreichen. Mündet das Konjunkturpaket II in eine Schuldenbremse, sind nötige Investitionen von morgen, wie Hochschulpakt und Exzellenzinitiative, in Gefahr.

Formale Strukturen und Verfahren des politischen Systems in Deutschland haben sich durch die Digitalisierung nicht radikal verändert, analysiert Politikwissenschaftlerin Lena Ulbricht. Größere Veränderungen gibt es stattdessen bei der unmittelbaren Arbeit der Akteure, die das politische System prägen.

Scientific, political and bureaucratic elites use epistemic practices like "big data analysis" and "web scraping" to create representations of the citizenry and to legitimize policymaking. I develop the concept of "demos scraping" for these practices of gaining information about citizens (the "demos") through automated analysis of digital trace data which are re-purposed for political means. This article critically engages with the discourse advocating demos scraping and provides a conceptual analysis of its democratic implications. It engages with the promise of demos scraping advocates to reduce the gap between political elites and citizens and highlights how demos scraping is presented as a superior form of accessing the "will of the people" and to increase democratic legitimacy. This leads me to critically discuss the implications of demos scraping for political representation and participation. In its current form, demos scraping is technocratic and de-politicizing; and the larger political and economic context in which it takes place makes it unlikely that it will reduce the gap between elites and citizens. From the analytic perspective of a post-democratic turn, demos scraping is an attempt of late modern and digitalized societies to address the democratic paradox of increasing citizen expectations coupled with a deep legitimation crisis.

Der Beitrag legt offen, dass Algorithmen, anders als häufig angenommen, nicht prinzipiell depolitisierend sind, sondern auch Anstoß für Politisierungsprozesse geben. Auf der Grundlage von vier Fallbeispielen aus den Bereichen Rechtsprechung, Sozialpolitik, Beschäftigtenkontrolle und Bonitätsprüfung wird dargelegt, dass Algorithmen sowohl zur Politisierung der 'materiellen' sowie der 'reflexiven' gesellschaftlichen Ordnung genutzt werden. ; This contribution argues that algorithms are not only depoliticizing, but can also serve as vehicles for politicization. Four examples from legal sanctioning, social policy, employee management and credit scoring point out that algorithms have created opportunities to politicize the 'material' as well as the 'reflexive' order of contemporary societies.

Hat der vielkritisierte deutsche Bildungsföderalismus auch positive Seiten und wirkt, wie die Föderalismustheorie annimmt, als Labor für die Entwicklung und Diffusion von Policy-Innovationen? Diese Frage wird anhand des Hochschulzugangs für beruflich Qualifizierte ohne Abitur untersucht. Die entsprechenden Regelungen waren lange Zeit Sinnbild der föderalen Uneinheitlichkeit, zeigen seit Mitte der 2000er-Jahre jedoch eine überraschende Konvergenz.Auf Grundlage einer Analyse mit standardisierten Daten sowie durch Prozessanalysen von politischen Entscheidungsprozessen zeigt sich, dass unter den Ländern durchaus erfolgreich erprobte Policy-Innovationen diffundieren und die Kultusministerkonferenz (KMK) die Diffusion fördert. Dennoch wird das produktive Potenzial des Bildungsföderalismus nur teilweise ausgeschöpft: Regionale Besonderheiten waren nicht der Ursprung der Policy-Innovation, und Harmonisierung stellte für die politischen Akteure kein treibendes Motiv dar

This article explores whether German Federalism acts as a 'laboratory' and pool of ideas for the dispersion of policy-innovations. The empirical analysis is centered on an educational policy and explores whether there are diffusion processes between the German states. The findings confirm the diffusion hypothesis and shed some light on the forms, the channels and the motives that account for the diffusion. Among others they point out the crucial role of the often criticized Standing Conference of the Ministers of Education and of non-state actors. Adapted from the source document.

Der Einsatz des Milliardensegens ist nicht geregelt - dass die Mittel den bedürftigsten Einrichtungen zukommen, darf bezweifelt werden. Die Ziele des Bildungsgipfels, etwa die Zahl der Schulabbrecher bis 2015 zu halbieren, wären nur durch langfristige Investitionen zu erreichen. Mündet das Konjunkturpaket II in eine Schuldenbremse, sind nötige Investitionen von morgen, wie Hochschulpakt und Exzellenzinitiative, in Gefahr.

AbstractResearch into "algorithmic discrimination" has largely dismissed the fact that algorithms are often developed and used by organizations. In this article, we show that organizational sociology can contribute to a more nuanced perspective on "algorithmic decision-making." Drawing on the concept of decision premises, we differentiate between various formal structures, particularly between different decision programs (conditional and purposive). This allows us to challenge two key assumptions, namely that human decision-makers rely heavily on algorithmically generated recommendations and that discrimination against protected groups needs to be solved mainly at the level of code.We identify the usefulness of distinguishing between conditional and purposive decision programs via a case study centered on the legal context: the risk assessment software "Correctional Offender Management Profiling for Alternative Sanctions" (COMPAS) that is employed in the US criminal justice system to inform judicial personnel about the recidivism risk of defendants. By analyzing the organizational structures, according to which the COMPAS score is formally and informally embedded in courts, we point out that the score represents an ambiguous and redundant information source for judges. The practice of minimizing the relevance of the score and decoupling it from the legal reasoning backstage particularly reflects the professional decision autonomy of judges, which is inherent in the legal system. The core finding of our approach is that strategies to reduce discrimination should not only scrutinize data quality or the statistical model but also consider the specific forms, functions, and consequences of the organizational structures that condition the ways in which discriminatory differences may or may not be (re)produced.

Research into "algorithmic discrimination" has largely dismissed the fact that algorithms are often developed and used by organizations. In this article, we show that organizational sociology can contribute to a more nuanced perspective on "algorithmic decision-making." Drawing on the concept of decision premises, we differentiate between various formal structures, particularly between different decision programs (conditional and purposive). This allows us to challenge two key assumptions, namely that human decision-makers rely heavily on algorithmically generated recommendations and that discrimination against protected groups needs to be solved mainly at the level of code. We identify the usefulness of distinguishing between conditional and purposive decision programs via a case study centered on the legal context: the risk assessment software "Correctional Offender Management Profiling for Alternative Sanctions" (COMPAS) that is employed in the US criminal justice system to inform judicial personnel about the recidivism risk of defendants. By analyzing the organizational structures, according to which the COMPAS score is formally and informally embedded in courts, we point out that the score represents an ambiguous and redundant information source for judges. The practice of minimizing the relevance of the score and decoupling it from the legal reasoning backstage particularly reflects the professional decision autonomy of judges, which is inherent in the legal system. The core finding of our approach is that strategies to reduce discrimination should not only scrutinize data quality or the statistical model but also consider the specific forms, functions, and consequences of the organizational structures that condition the ways in which discriminatory differences may or may not be (re)produced.

AbstractThis paper offers a critical synthesis of the articles in this Special Issue with a view to assessing the concept of "algorithmic regulation" as a mode of social coordination and control articulated by Yeung in 2017. We highlight significant changes in public debate about the role of algorithms in society occurring in the last five years. We also highlight prominent themes that emerge from the contributions, illuminating what is distinctive about the concept of algorithmic regulation, reflecting upon some of its strengths, limitations, and its relationship with the broader research field. In closing, we argue that the core concept is valuable and maturing. It has evolved into an analytical bridge that fosters cross‐disciplinary development and analysis in ways that enrich its early "skeletal" form, thereby enabling careful and context‐sensitive analysis of algorithmic regulation in concrete settings while facilitating critical reflection concerning the legitimacy of existing and proposed regulatory regimes.