The Political Economy of Social Impact: Understanding the Diffusion of Corporations’ Social Impact Norms – NOW FILLED

Contact: Adam Chalmers


Department: Political Economy

Institution: King’s College London

Project timeline: April to July 2021

Project duration: Semi-part time (flexible) for a maximum of 13 weeks-equivalent work over a four-month period (April to July 2021)

Closing date:  this internship has now been filled by Constance Woollen

Expertise: The ideal candidate will have very good quantitative research skills including (1) advanced knowledge of statistical analysis and (2) a working knowledge of text mining, natural language processing, and text-as-data analysis. They should also have experience building and managing large datasets as well as developing and applying coding schemes. Excellent writing and organisational skills are also required.

Project description: Our project seeks to better understand the role of the state as a driver of corporations’ social impact: the effect (positive or negative) that a business has on their own workforce, their local community, the environment, and wider society. Importantly, existing scholarship has largely side-lined the state in this regard and a near consensus in the literature has formed around the notion that the state has retreated from regulating its own domestic multinational firms. Corporations are thought to have instead become their own champions of advancing positive social impact. We carried out a short pilot study in 2019 systematically investigating these assumptions. Our initial findings challenge this consensus view and paint a far more nuanced picture of the role of the state as a driver of corporate social impact. These findings frame two main research question clusters that define the aims of our project. (1) Are states ‘norm makers’ or ‘norm takers’ in the diffusion of global social impact norms? For instance, where and when do we see global impact standards, like the UN Global Compact, downloaded into state law? Alternatively, when are existing state norms actively uploaded into global norms? Do states sometimes bypass the global level, and instead cross-load norms with other states and do we see patterns of regional clustering around a norm-leader? (2) How can we account for variation in the ‘restrictiveness’ of state-driven social impact guidelines? Are states captives to their largest industries or multinationals? Are some aspects of social impact simply harder to quantify and regulate than others? How do regional races to regulatory top and bottom factor in?

Description of work involved: The student will engage three main tasks. The first task is to help expand the dataset and build our corpus of documents. This will include organising and collecting state social impact guidelines from four sources: Carrots and Sticks, Principles for Responsible Investing, the Sustainable Stock Exchanges Initiative, and the European Corporate Governance Institute. The second task involves analysing these documents. This will include some hand-coding using the Comparative Agendas Project coding scheme but will primarily involve using various text-as-data techniques (e.g., creating taxonomies and calculating term frequency statistics; estimating cosine similarity scores and using these in path analysis to test diffusion effects). The third task is writing up results and drafting a paper co-authored with the two principle investigators. This will likely involve drafting parts of the literature review or methods section as well as working on the statistical appendix.

Student benefits: The main benefit is publishing a co-authored paper with the Principle Investigators. This will add to the student’s CV and will help them in a competitive job market where publications play a major role. Second, the student will benefit from learning new methodological skills and adding to their methodology-toolkits. Text mining, natural language processing, and text-as-data analysis are increasingly becoming critical skills as social science and public policy make a turn toward big data. Third, the student will have an opportunity to expand their network in academia. This will result from working with the two Principle Investigators and others working on the project (including a LISS-DTP PhD student) as well as from presenting their work at international conferences.

The successful candidate can expect to receive specific training in text mining, natural language processing, and text-as-data analysis as part of this internship (in the specific areas where these skills are lacking). These are increasingly important and transferable quantitative skills that would prove useful for any budding academic or individuals seeking jobs in public policy, government, or think tanks.