Language legislation in Ireland and the United Kingdom: Exploring the gaps between theory and practice
Bibliographic record
Abstract
The central objective in this thesis is to explore the gaps between the normative justifications advanced for language rights and language legislative protection and the effective realisation of those rights and legislative provisions in practice. This objective is achieved by examining the scope and application of language rights and legislative provisions within language legislation in Ireland and the United Kingdom. Drawing on Canadian jurisprudence advocating for language rights to be recognised as “purposeful”, the thesis considers the extent to which Ireland and the United Kingdom have limited the acceptance of positive obligations as they relate to the provision of language services in the public sphere. In arguing that language rights are distinct in nature, the thesis suggests that in order for language rights to be effectively realised, an approach to language rights and language legislation more generally must be underpinned by a substantive vision of equality, otherwise language rights and legislative provisions merely amount to symbolic recognition and vacuous rhetoric as opposed to being substantive and enabling rights and provisions. Having said that, the thesis also recognises and elucidates the practical difficulties that arise in the realisation of language rights and language legislative provisions and in doing so seeks to stimulate further dialogue about the nature and limits of language rights and language legislation.
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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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".