Critical understanding of predictive policing
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Abstract
Ragnar Nurkse Department of Innovation and Governance is opening a doctoral position in the area of 'Critical understanding of predictive policing' within NordForsk project. The project should focus on research that contributes to establishing transparency and set an epistemological standard for the investigation of innovative data-based policing.
| Research field: |
Public policy and innovation |
|---|---|
| Supervisors: |
Prof. Dr. Anu Masso Prof. Dr. Ahti-Veikko Pietarinen |
| Availability: | This position is available. |
| Offered by: |
School of Business and Governance Ragnar Nurkse Department of Innovation and Governance |
| Application deadline: | Applications are accepted between November 15, 2021 00:00 and December 15, 2021 23:59 (Europe/Zurich) |
Description
There are three key inter-related research themes we are interested in:
- Profiling in predictive policing, using the example of gene data. As the DNA genealogical databases are a valuable source for police, there are no universal rules in using these data in predictive policing. The potential understandings of the use of genetic data for predictive policing purposes and international police regulations of genetic biohacking, individuals' experimentations with their symbolic and physical (boundaries), are to be examined.
- Digital migration control through data. The digital migration (e.g., enabled by Estonian e-residency) has no physical residency assumption, but traditional migration policy's selectivity principles tend to be implemented in the policy instruments. The predictive datafied police solutions are implemented for classifying the applicants, but the selection mechanisms are not known.
- Automated solutions for predictive border control. The legal agencies implement facial recognition algorithms to identify travelers crossing the borders, classify wanted criminals, and predict crimes. The understanding of the social diversities of the human decision-makers who use the predictive border control tools is unknown.
The researcher should complete his / her research results in peer-reviewed articles published in internationally recognized journals. The research plan should also be in line and contribute to the strategic research axes of the Nurkse Department and its members. The ideal ratio between autonomous, independent research and the contribution of upcoming PhD students to joint research with other members of the Department is 50-50. As part of his / her path, the PhD student is also expected to gain teaching, supervision, and research management experience at the Nurkse Department. In this respect, courses, workshops, seminars, and inductions will be provided, to which new researchers are encouraged to attend and contribute.
A successful candidate should preferably have:
- A MA degree in social sciences;
- Expertise in qualitative or quantitative, digital or computational research methods; knowledge in or readiness to use experimental study design and cognitive methods (eye-tracking) is an advantage;
- A clear interest in and clear vision for independent research concerning the chosen topic;
- Excellent command of English and Estonian languages;
- Strong and demonstrable writing and analytical skills;
- Capacity to work both as an independent researcher and as part of an international team; Ability and willingness to assist in organizational tasks relevant to the project.