The SWDTP has the following steers from the ESRC
- 3 studentships to be awarded for Data Skills (applicants are eligible from any of our disciplinary or interdisciplinary pathways, except for AQM)
- 3 studentships to be awarded to AQM (applicants must have applied to the AQM pathway)
Should I apply for the Advanced Quantitative Methods (AQM) pathway or the data skills steer?
Both the AQM pathway and the data skills steer are intended to advance and to showcase the application of quantitative methods or ‘new’ forms of digital data to social scientific research and enquiry. They have in common that both should go beyond the routine and the conventional, to be offering something that is original and innovative, relative to the discipline and topic. Neither is about using tried-and-tested methods of analysis or forms of data collection. They are both exploring something novel. However, they differ in terms of their focus, with AQM’s being on advanced quantitative methods, and data skills’ on data. Whilst AQM is exclusively quantitative, the data skills steer could involve, for example, the digitisation and use of more qualitatively generated data.
The table below is to help you determine whether your research proposal is ‘in scope’ for either AQM or the data skills steer. You cannot apply for both. To use it, start at (1) in the top left, answer the question to its right, and then move on to another row in the table in accordance with your answer. For example, if you answer yes to the question in row (1), move down to the question in row (2). If you answer no, go to row (4).
As you go through the table, ask yourself, “is it (a) the methods or (b) the data that are core to my project, or (c) are neither really core?”, and “is what I am proposing going beyond the ‘everyday’ use of methods or data in my field of study?” Those and the questions in the table should guide you to a conclusion. No guidance, however, can consider every eventuality so, if you are uncertain, please contact swdtp-enquiries@bris.ac.uk for advice.
| START HERE: | ||
| (1) | Does you research involve the production and/or analysis of machine-readable, digital data, whether from quantitative or qualitative sources? | If YES go to (2) If NO, go to (4) |
| (2) | Are the data and/or the methods applied to them foundational (not just secondary) to the purposes of the research, forming a core component of the research project? | If YES go to (3) If NO, go to (4) |
| (3) | Is a key focus of the research on: (A) developing or applying quantitative methods (e.g. statistical, econometric, machine-learning, etc.) to achieve the research goals, where the innovation is in those methods and/or their application; (B) the data, where the innovation is in (a) ‘harvesting’, ‘scraping’, linking or generating data in ways that are novel, and need not be exclusively quantitative, or (b) that utilise ‘big’, administrative, harder-to-access (e.g. secure) or unconventional sources of data; or, (C) using conventional sources of data, and/or well-established methods of data collection (e.g. surveys, standard data logging) or analysis (e.g. regression) to help answer the research questions. | If (A) go to (5) If (B) go to (10) If (C) go to (4) |
| (4) | Sorry, this is not eligible for either the AQM pathway or the data skills steer. Please direct your application to one of our ‘standard’ studentships and pathways instead. | END |
| IS IT ADVANCED QUANTITATIVE METHODS (AQM)? | ||
| (5) | Are the methods quantitative and can they be regarded as advanced relative to the discipline/pathway to which you are applying, and to the field of study? | If YES go to (6) If NO go to (9) |
| (6) | Does the research project, and its main goals and objectives, clearly fall under the rubric of quantitative social science (being clearly identifiable as, at minimum, 50% social science)? | If YES go to (7) If NO go to (9) |
| (7) | Could you research project be characterised as mixed methods, with a sizeable qualitative component? | If YES go to (9) If NO go to (8) |
| (8) | Consider applying to the AQM pathway. | END |
| (9) | Sorry, this is unlikely to be eligible for the AQM pathway. It is also unlikely to be eligible for the data skills steer. Consider directing your application to one of our ‘standard’ studentships and pathways instead. | END |
| IS IT DATA SKILLS? | ||
| (10) | Can the research be characterised as data-based, data-driven, or as incorporating ideas, methods or techniques drawn from data science? | If YES go to (11) If NO go to (15) |
| (11) | Can the sources, extraction of or creation of the data be characterised as novel or presently underutilised? | If YES go to (12) If NO go to (15) |
| (12) | Is an important component of the research project about exploring how to create or operationalise the data to answer the research questions? | If YES go to (13) If NO go to (15) |
| (13) | Are the data important for most or all of your research project’s aims and objectives? | If YES go to (14) If NO go to (15) |
| (14) | Consider applying to the Data Skills steer. | END |
| (15) | Sorry, this is unlikely to be eligible for the Data Skills steer. It is also unlikely to be eligible for the AQM pathway. Consider directing your application to one of our ‘standard’ studentships and pathways instead. | END |