Getting to the Frontiers: Methodologies
Bibliographic record
Abstract
Introduction Policing and security research has increased dramatically in the past two decades. This has happened across disciplines in which qualitative inquiry is prevalent, including criminology. Simultaneously, the reach and scope of existing policing and security agencies has been widening, often through new laws granting greater powers of search, surveillance, arrest and detention beyond their traditional purview (Ericson, 2007; Earl, 2009). Some agencies and agents remain understudied despite long histories; many other new ones have yet to be studied. On police and security frontiers, the agencies are becoming more networked and are increasingly collaborating and sharing information that identifies risky spaces and persons consistent with their evolving and sometimes expanding mandates. This chapter is about getting to policing and security frontiers, and it focuses on methodologies developed to accomplish this travel. We explore elements of qualitative research on policing and security agents on frontiers of thinking and practice. This includes freedom of information (FOI) requests, which are a cutting-edge method and thus befitting research on frontiers. The chapter discusses ways of accessing and moving on to frontiers to study forms of policing and security elaborated in other chapters, as well as common barriers encountered on the way and strategies to circumvent them. While it is often assumed that policing and security agencies and agents, including those operating on frontiers, are difficult to access due to their clandestine, bureaucratic or obscure nature, this chapter argues that this is not necessarily the case. Unlike the Northwest Mounted Police's much celebrated Great March West to a Canadian frontier, the subject of numerous books and even police museums (see Chapter Seven), and repeated in other colonial nations consistent with their mythologies, getting to policing and security frontiers is far chancier and more mundane for researchers. It is less a grand, straight-line, disciplined march, and more an improvisational dance. If, as Greene (2014) puts it, research on and with policing (and security) agencies is like trying to master the tango, then the growing networking and reach of these agencies is adding erratic beats and requiring fancier footwork among researchers to be allowed into their frontier dancehalls.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".