Politics of Sustainability in Public Health – data-driven critical conceptual analysis
The course draws attention to the power of key concepts in the sustainability agenda and more specially, how such concepts have come to accommodate various and sometimes conflicting ideological messages. Concepts such as sustainability, empowerment, partnership and resilience can for instance reflect both an urge for global solidarity and a requirement for self-management and improvement. The course engages participants in critical reflection about how concepts and their divergent and sometimes conflicting meanings impact how we frame and address public health and sustainability issues, thus fostering understanding of how socio-political processes affect environmental and health processes.
An important method used in the course is data-driven critical conceptual analysis based on corpora. The development of free, open-access corpora and corpus analysis tools enables students and researchers anywhere in the world to question and investigate the semantic and affective meaning of the concepts they use in everyday language and that they tend to take for granted. This is a particularly powerful, but as yet underused resource by scholars in public health and critical sustainability studies.
The course offers a rare and valuable opportunity for students with many different backgrounds to work together to gather and analyse data, explore areas of agreement and disagreement, and develop a more nuanced appreciation of the diversity of meanings that may be attributed by different people to the same concept.
After having completed the course, actively participated in seminars, workshops and group work, you are expected to:
- outline/explain the political and ideological implications of the choice of terminology in sustainability discourses;
- describe/summarize existing corpora/sub-corpora, and suitable tools for their analysis
- outline/explain theoretical approaches to the understanding and analysis of conceptual and discursive power in public health.
After having completed the course, actively participated in seminars, workshops and group work, you are expected to be able to:
- identify patterns in linguistic data and explain how they affect the semantic and affective properties of concepts
- offer a critical explanation of the implications of linguistic patterns for the politics of sustainability
- use corpus analysis tools effectively to analyse textual data and key concepts in the sustainability agenda
- analyse the power inherent in language and concepts and how language and concepts impact public health decisions
- address complex questions based on collective, live analysis of data/corpora in a datathon setting
After having completed this course you should be able to:
- communicate your own subject knowledge to peers outside your discipline
- cooperate productively with peers from different areas of expertise
- present your results clearly to a non-expert academic audience
- elaborate a convincing argument to explain the significance of the results of conceptual analysis
- carry out research in interdisciplinary teams
- offer reasoned justifications for the choice of terminology in sustainable development
- critique taken-for-granted, singular definitions of key concepts that do not attend to disciplinary and cultural diversity;
- reflect on your own research and dissemination practice.
The course will recruit two groups of students: (1) Master’s students in Public Health Science and epidemiology and other master’s students from the Institute of Health and Society (max 20 students) and (2) Master students in any discipline from the Circle U partner institutions (max 20 students).
Registered on 1) the master’s programme in Public Health Science and epidemiology and other master’s programmes at the Institute of Health and Society (UiO, MED) OR 2) a masters level programme at a Circle U university.
- For students registered at the master’s programme in Public Health Science and epidemiology and other master’s programmes at the Institute of Health and Society (UiO, MED) the following requirements apply:
- Familiarity with non-subject specific academic language in English is require
- For master’s students in any discipline from the Circle U partner institutions the following requirements apply:
- You must have a bachelor’s degree comparable to a Norwegian bachelor’s degree.
- You must be enrolled in a master’s programme at a Circle U partner institution.
- You must have a minimum grade average comparable to a Norwegian C in the required specialization. A Norwegian C is described as a good grade, generally comparable to an American B and an Upper Second Class in the British system.
- Familiarity with non-subject specific academic language in English is required.
- You must justify your interest in the topic of the course through a motivation letter, with reference to previous experiences from work and/or studies.
Each partner institution nominates 2 students (and 1 on a waiting list) from their institution based on the criteria above.
Teaching will be organized as a one-week intensive on-site course. Students will attend a lecture on the broad subject of sustainability as it applies to public health, to be delivered by a guest lecturer on an area of their expertise as a way of starting a discussion among students. The visiting lecturer will remain available throughout the week for consultation. During the first three days, hands-on datathon sessions on corpus analysis involving the whole cohort will be run and supervised by tutors in the morning, and research seminars on corpus-based conceptual analysis will be delivered by expert researchers in the afternoon. Tutors will work with students to form teams based on similar interests and assist them in drawing up a brief project outline on the third day. Students will then work in datathon groups, under the supervision of a mentor, during the last two days.
Each team of students will deliver a 10-15 minute verbal presentation on the last day of the course. Each student will additionally submit a 2000-word project report presenting his/her data, analysis and discussion one month after the end of the course.