Visual and textual narratives of conflict-related displacement in Northern Ireland
Bibliographic record
Abstract
Combined textual and visual narratives and counternarratives illustrate a range of experiences in Northern Ireland’s conflictual, spatial landscape. In this article, I argue that combined textual and visual narratives about conflict-instigated displacement create and articulate community-specific experiences of disadvantage, with the intention of gaining political recognition and/or advantage over other communities in ongoing processes of conflict transformation. I expose the multiple, contextualised meanings of selective narratives that are accessible in language and image but, that are rarely questioned because of the political influence of their tellers or, because of their scale. Their meanings and intentions exist alongside counternarratives about intra-community displacement and displacement against other groups and are concurrent with public apathy, which serve to minimise their effectiveness as political tools to gain community-specific, social and political advantage. These narratives and counternarratives persist as key spatial markers and as sites on which conflict, and its effective transformation, are played out.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".