95698 - Social Studies of Science and Technology (1) (Lm)

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education Gender equality Industry, innovation and infrastructure

Academic Year 2021/2022

Learning outcomes

At the end of the course students will have knowledge of the main concepts and approaches developed by science and technology studies (STS), and can analytically compare them and discuss their pros and cons; they will understand basic issues about the materiality of and governance by data infrastructures and their social implications, and will have developed basic experience in designing an empirical research on data infrastructures

Course contents

The course provides an introduction to the social studies of science and technology (STS), with a focus on data infrastructures. STS are a long-standing research field which has developed perspectives to address scientific and technological development by using epistemologies, heuristic tools and methods from ethnography, sociology, history, philosophy and semiotics. The course draws the roots of the field in R. Merton’s sociology of science and T. Kuhn’s structure of scientific revolutions, to then focus on the Sociology of Scientific Knowledge (SSK), the Social Construction of Technology (SCOT) and Actor-Network Theory (ANT). These approaches are studied with the support of hands-on exercises and empirical case studies (weeks 1-3).

In the second part we focus on data infrastructures. We will address some aspects of the materiality of and governance by data infrastructures, including their sociopolitical implications. All these topics are tackled by reading, presenting and commenting leading international literature and empirical case studies.

Throughout the course, interactive moments are devoted to developing empirical research design skills, ranging from research question design to research methodologies. Such moments are finalized to support the STS research design to be submitted as part of the course assessment.

Week 1 – Merton and the Sociology of Science, Kuhn and the Structure of Scientific Revolutions

Week 2 – The Sociology of Scientific Knowledge (SSK) and Social Construction of Technology (SCOT)

Week 3 – Actor-Network Theory (ANT), or the sociology of translation

Week 4 – Evolutionary approaches, the Materiality of data infrastructures

Week 5 – Governance by Data Infrastructures: Information infrastructures and classification, Code as Law, Critical data studies

Readings/Bibliography

The reader is made of journal articles and book chapters. They are all available on Virtuale or through the UniBO digital library (AlmaRE). See Virtuale for reader details and copies of the material.

 

Week 1 – Introduction; Merton and the Sociology of Science; Kuhn and the Structure of Scientific Revolutions

Law, J. (2015)

Merton, R. (1942), Sismondo, S. (2010), Chap. 3

Kuhn, T. (1962, Sismondo, S. (2010), Chap. 2


Week 2 – The Sociology of Scientific Knowledge (SSK); the Social Construction of Technology (SCOT)

Pinch, T. J., & Bijker, W. E. (1984)

Bijker, W.E. (1987)

Recommended reading:

Spitz, D. & Hunter, S.D. (2005)

 

Week 3 – Actor-Network Theory (ANT), or the sociology of translation

Callon, M. (1986)

Latour, B. (1992)

Law, J. (2007)

 

Week 4 – STS and communication studies; the Materiality of data infrastructures

Dourish, P. (2017)

Recommended:

Boczkowski, P., & Lievrouw, L. A. (2008)

Bijsterveld, K. (2014).

 

Week 5 – Governance by Data Infrastructures: Information infrastructures and classification, Code as Law, Critical data studies

Bowker, G.C. and Star, S.L. (1999)

Lessig, L. (2006)

Suchman, L. (1994)

Gitelman (2013)

Recommended reading:

Pelizza (2016)

Teaching methods

The teaching style favours interactivity. Classes include lectures by the teacher, presentations by students and class discussions.

The aim of presentations is threefold: 1) to support and develop students’ understanding of the literature; 2) to support and develop students’ analytical and research skills before the formal evaluation; 3) to trigger peer-learning.

To achieve these goals, the draft reports that are to be submitted for the final evaluation will be preliminary and collectively discussed in class (see assessment methods).

Assessment methods

The learning process is assessed against two written texts. The first (interim) consists in a comparative analysis of a given case study using SCOT and ANT. The second (at the end of the course) consists in an STS empirical research design. Drafts of both texts are preliminarily and collectively discussed in class.

Teaching tools

Classes are conducted in blended modalities: in class, computer with video beamer and digital whiteboard. Interactive software to facilitate classroom exchange. Online: Teams functionalities including chat, turn administration, screen sharing.

The teaching material consists of the reader texts, the presentations prepared by the teacher and the case studies, including artefacts to be analysed in class (eliciting tools). When not protected by copyright, the teaching material is made available to students through the Virtuale teaching platform of the University of Bologna. Copyrighted texts in the reader are available at the FILCOM library and at other libraries of the University of Bologna.

Office hours

See the website of Annalisa Pelizza