Localism — call it the Y factor: The Gaeltacht Quarter and the East End have got talent, so Y not use it?
Bibliographic record
Abstract
Every moment in a life contains a multitude of small localised choices which themselves lead to a multitude of other possible choices. The Burning of Bombay Street in 1969 offered a split in the road: in one direction, there was hostility, hurt, harm; in another, something more constructive, positive and empowering. Bricks were lifted not to be thrown, but to be placed next to another and another. In this way, homes were built, a street emerged, a community was re-created, and the ambition of Belfast’s Irish-language community began to take root. Their ‘can do’ movement established the Gaeltacht Quarter, with its nursery, primary and secondary schools, social clubs, small and large businesses, book stores, shops, cafés and a radio station. The pulse of today’s changing Belfast is taken from here. But this is no look back: the mirror tells us what is behind, but what lies ahead is the goal of this paper: the continuing potential for connections between what people dared to achieve in the past and what they can achieve today.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.024 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".