The Languages Acts in the Republic of Ireland and Canada: lessons to be learnt by Northern Ireland
Bibliographic record
Abstract
Linguistic and socio-linguistic texts consistently reiterate the importance of language as a vital aspect of self-identity and ethnicity.'It is for this reason that languages, and specifically minority languages, need to be protected.In Northern Ireland, the Irish language has a complicated sociocultural heritage.It is not a "state language," nor indeed is it one that is respected by many state politicians.The language enjoys little state protection, legal or otherwise.Education programmes and language maintenance programmes provide insufficient incentives to speak and enjoy the language.As a result, Irish has been eroded almost entirely from the communal value system of a whole community of speakers.This erosion has itself been accelerated by the overt politicisation of language in Northern Ireland, resulting in relatively minimal use outside the education arena and a social marginalisation of the language within Northern communities.Officially, the position of the Irish language has significantly improved since the 1970s, with little overt hostility from official sources.This is due, particularly, to its protection under the Belfast Agreement 1998 and under the European Charter for Regional or Minority Languages 19922 Despite this strength in theory, the reality is much less benign and, perhaps, much more invidious.Irish in Northern Ireland has traditionally been perceived as a threat and a political device capable of polarising rather than bringing about positive effects.Similarly, the English language is itself, a political tool.One need only look at the tribal "branding" in use in Northern Ireland, such as the * LLB, LLM (Dub), BCL Candidate, University of Oxford.The author wishes to acknowledge with appreciation the support given by his LLM supervisor, Dr Catherine Donnelly.Her expertise, knowledge and committed guidance contributed considerably to this article.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".