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This text is a contribution to the research on the worldwide success of evangelical Christianity and offers a new perspective on the relationship between late modern capitalism and evangelicalism. For this purpose, the utilization of affect and emotion in evangelicalism towards the mobilization of its members will be examined in order to find out what similarities to their employment in late modern capitalism can be found. Different examples from within the evangelical spectrum will be analyzed as affective economies in order to elaborate how affective mobilization is crucial for evangelicalism’s worldwide success. Pivotal point of this text is the exploration of how evangelicalism is able to activate the voluntary commitment of its members, financiers, and missionaries. Gathered here are examples where both spheres—evangelicalism and late modern capitalism—overlap and reciprocate, followed by a theoretical exploration of how the findings presented support a view of evangelicalism as an inner-worldly narcissism that contributes to an assumed re-enchantment of the world.
Moving Forces
(2017)
Throughout a large part of the twentieth century, the body was interpreted as a field of signs, the meaning of which pointed to an unconscious dimension. At the height of the popularity of structuralism, Jacques Lacan deemed the unconscious to be “structured like a language.” Starting in the early 1990s, however, a deep shift occurred in the way the body was interpreted. A new movement cast tremendous doubt on the hegemony of language and instead advocated a performative, pictorial, and affective approach — the so-called material turn — which encompassed all of these. In the words of Karen Barad, this turn inquired as to why meaning, history, and truth are assigned to language only, whereas the movements of materiality are given less prominence: “How did language come to be more trustworthy than matter? Why are language and culture granted their own agency and historicity while matter is figured as passive and immutable?” With this shift toward the material, bodies began to be seen in a different light and their materiality understood as something that follows its own laws and movements, which cannot be understood exclusively in terms of social-cultural codes. Instead, these laws and movements call into question the very dichotomies of nature/culture and body/spirit.
Dropping Out or Keeping Up?
(2016)
The aim of this study was to examine how automatic evaluations of exercising (AEE) varied according to adherence to an exercise program. Eighty-eight participants (24.98 years ± 6.88; 51.1% female) completed a Brief-Implicit Association Task assessing their AEE, positive and negative associations to exercising at the beginning of a 3-month exercise program. Attendance data were collected for all participants and used in a cluster analysis of adherence patterns. Three different adherence patterns (52 maintainers, 16 early dropouts, 20 late dropouts; 40.91% overall dropouts) were detected using cluster analyses. Participants from these three clusters differed significantly with regard to their positive and negative associations to exercising before the first course meeting (η2p = 0.07). Discriminant function analyses revealed that positive associations to exercising was a particularly good discriminating factor. This is the first study to provide evidence of the differential impact of positive and negative associations on exercise behavior over the medium term. The findings contribute to theoretical understanding of evaluative processes from a dual-process perspective and may provide a basis for targeted interventions.
Dropping Out or Keeping Up?
(2016)
The aim of this study was to examine how automatic evaluations of exercising (AEE) varied according to adherence to an exercise program. Eighty-eight participants (24.98 years ± 6.88; 51.1% female) completed a Brief-Implicit Association Task assessing their AEE, positive and negative associations to exercising at the beginning of a 3-month exercise program. Attendance data were collected for all participants and used in a cluster analysis of adherence patterns. Three different adherence patterns (52 maintainers, 16 early dropouts, 20 late dropouts; 40.91% overall dropouts) were detected using cluster analyses. Participants from these three clusters differed significantly with regard to their positive and negative associations to exercising before the first course meeting (η2p = 0.07). Discriminant function analyses revealed that positive associations to exercising was a particularly good discriminating factor. This is the first study to provide evidence of the differential impact of positive and negative associations on exercise behavior over the medium term. The findings contribute to theoretical understanding of evaluative processes from a dual-process perspective and may provide a basis for targeted interventions.
The aim of this study was to examine how automatic evaluations of exercising (AEE) varied according to adherence to an exercise program. Eighty-eight participants (24.98 years +/- 6.88; 51.1% female) completed a Brief-Implicit Association Task assessing their AEE, positive and negative associations to exercising at the beginning of a 3-month exercise program. Attendance data were collected for all participants and used in a cluster analysis of adherence patterns. Three different adherence patterns (52 maintainers, 16 early dropouts, 20 late dropouts; 40.91% overall dropouts) were detected using cluster analyses. Participants from these three clusters differed significantly with regard to their positive and negative associations to exercising before the first course meeting (eta(2)(p) = 0.07). Discriminant function analyses revealed that positive associations to exercising was a particularly good discriminating factor. This is the first study to provide evidence of the differential impact of positive and negative associations on exercise behavior over the medium term. The findings contribute to theoretical understanding of evaluative processes from a dual-process perspective and may provide a basis for targeted interventions.
Between-School Variation in Students' Achievement, Motivation, Affect, and Learning Strategies
(2017)
To plan group-randomized trials where treatment conditions are assigned to schools, researchers need design parameters that provide information about between-school differences in outcomes as well as the amount of variance that can be explained by covariates at the student (L1) and school (L2) levels. Most previous research has offered these parameters for U.S. samples and for achievement as the outcome. This paper and the online supplementary materials provide design parameters for 81 countries in three broad outcome categories (achievement, affect and motivation, and learning strategies) for domain-general and domain-specific (mathematics, reading, and science) measures. Sociodemographic characteristics were used as covariates. Data from representative samples of 15-year-old students stemmed from five cycles of the Programme for International Student Assessment (PISA; total number of students/schools: 1,905,147/70,098). Between-school differences as well as the amount of variance explained at L1 and L2 varied widely across countries and educational outcomes, demonstrating the limited generalizability of design parameters across these dimensions. The use of the design parameters to plan group-randomized trials is illustrated.
Between-school variation in students' achievement, motivation, affect, and learning strategies
(2017)
To plan group-randomized trials where treatment conditions are assigned to schools, researchers need design parameters that provide information about between-school differences in outcomes as well as the amount of variance that can be explained by covariates at the student (L1) and school (L2) levels. Most previous research has offered these parameters for U.S. samples and for achievement as the outcome. This paper and the online supplementary materials provide design parameters for 81 countries in three broad outcome categories (achievement, affect and motivation, and learning strategies) for domain-general and domain-specific (mathematics, reading, and science) measures. Sociodemographic characteristics were used as covariates. Data from representative samples of 15-year-old students stemmed from five cycles of the Programme for International Student Assessment (PISA; total number of students/schools: 1,905,147/70,098). Between-school differences as well as the amount of variance explained at L1 and L2 varied widely across countries and educational outcomes, demonstrating the limited generalizability of design parameters across these dimensions. The use of the design parameters to plan group-randomized trials is illustrated.
Affect Disposition(ing)
(2018)
The “affective turn” has been primarily concerned not with what affect is, but what it does. This article focuses on yet another shift towards how affect gets organized, i.e., how it is produced, classified, and controlled. It proposes a genealogical as well as a critical approach to the organization of affect and distinguishes between several “affect disposition(ing) regimes”—meaning paradigms of how to interpret and manage affects, for e.g., encoding them as byproducts of demonic possession, judging them in reference to a moralistic framework, or subsuming them under an industrial regime. Bernard Stiegler’s concept of psychopower will be engaged at one point and expanded to include social media and affective technologies, especially Affective Computing. Finally, the industrialization and cybernetization of affect will be contrasted with poststructuralist interpretations of affects as events.
Affect Disposition(ing)
(2018)
The “affective turn” has been primarily concerned not with what affect is, but what it does. This article focuses on yet another shift towards how affect gets organized, i.e., how it is produced, classified, and controlled. It proposes a genealogical as well as a critical approach to the organization of affect and distinguishes between several “affect disposition(ing) regimes”—meaning paradigms of how to interpret and manage affects, for e.g., encoding them as byproducts of demonic possession, judging them in reference to a moralistic framework, or subsuming them under an industrial regime. Bernard Stiegler’s concept of psychopower will be engaged at one point and expanded to include social media and affective technologies, especially Affective Computing. Finally, the industrialization and cybernetization of affect will be contrasted with poststructuralist interpretations of affects as events.