Organizations, order, and peace: policing Northern Ireland in the aftermath of Brexit
Bibliographic record
Abstract
Despite an extensive literature on security sector reform processes after conflict, there is little recognition that peacebuilding is an organisational, as well as a political endeavour (Murphy et al, 2018). This paper explores the experience of the Police Service of Northern Ireland, located within a long running ethno political conflict, and still unsettled in its organisational identity and history. While the past twenty years have seen enormous change in policing in Northern Ireland, the ‘new beginning to policing’ envisioned by the post agreement Independent Commission on Policing has not been fully realised (Ellison, 2007). Though significant aspects of the change have been successful, there remain serious and enduring challenges that suggest the organisation is still a significant distance from the original transformative aims (Murphy, 2019). The system change represented by Brexit has heightened political uncertainty and refocused attention on the ongoing security threat. All these factors raise both operational risk and challenges to inclusive policing. We argue that having embarked upon a process of change, the police in Northern Ireland are trapped in liminal space – unable to move forward to ‘ordinary’ policing and unsure how to respond to a renewed threat. The paper draws on data from seventy separate interviews with participants within the Northern Ireland policing sector, their advisors and other key stakeholders over a period of thirteen years (2002-2015). The research approach adopted was process based and longitudinal utilizing a single case study method, with a concern for explanatory analysis (Pettigrew 1990, Yin 1993, Yin 2003). Of the seventy interviews conducted, roughly two thirds were with individuals directly associated with the policing change process. The rest were representatives of NGOs, journalists, politically active participants and advisors, senior individuals associated the voluntary sector, academics or community relations and mediation professionals who had engaged with the organisation at different stages with the clear objective of creating lasting change (Dawson, 2003).<br/><br/>Ellison, G. (2007). A Blueprint for Democratic Policing Anywhere in the World? Police Quarterly, 10(3), 243-269<br/>Murphy, J., McDowell, S., Braniff, M. & Denyer, D. (2018), Managing contested spaces: Public managers, obscured mechanisms and the legacy of the past in Northern Ireland Environment and Planning C: Government and Policy. 36, 3<br/>Murphy, J., (2017), Leading through Conflict and Change: Chief Constables in Northern Ireland, in Leading the Police: A History of Chief Constables. Stevenson, K., Cox, D. J. & Channing, I. (eds.). Routledge, (Routledge SOLON Explorations in Crime and Criminal Justice Histories).<br/><br/>
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".