Bibliographic record
Abstract
The literary critic and commentator Edna Longley has written about Northern Ireland as a ‘cultural corridor’, a space through which both Irishness and Britishness travel and intermingle (Longley 1993). Such a territory is by its nature home to colliding political identities, national aspirations and battles for power. In Northern Ireland the outcome was a long and violent political conflict, referred to colloquially as ‘the Troubles’. In such a complex, difficult and dangerous environment, policing has always been a critical (some would say, the critical) issue of engagement. For a long period of time, each community saw, reflected in their relationship with the police, their own national identity either protected, or rendered illegitimate by the state. In this way the culture, politics and organisational identity of the RUC were derived from, and intimately bound up with the structural dimensions of the conflict itself: institutions, equality, loyalty, representation, defence, justice. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.085 |
| Scholarly communication | 0.029 | 0.018 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".