Коммуникативные стратегии самоидентификации североирландцев (на материале региональных аналитических блогов и новостных сайтов)
Bibliographic record
Abstract
The article touches upon one of the typical contemporary world problems, namely the problem of ethnic, cultural, and political self-identification. The problem in question results from two current tendencies on the one hand, a tendency towards globalization and unification, and on the other hand, a tendency towards autonomy and separation. The issue is vital for multi-cultural and multi-ethnic states, such as Spain, Belgium, Canada, and the United Kingdom. A trigger which brought the problem to the forefront was the Scottish Referendum of 2014, since when a lot of cultural and political movements in the aforementioned states have become more active than they used to be. In the United Kingdom alone, the referendum influenced not only life in Scotland, but in the other home nations, among which is Northern Ireland. Northern Ireland has traditionally been a part of the United Kingdom which has to regulate its policies according to what’s happening in the rest of Great Britain and in the Irish Republic. Cultural and political trends have always been well reflected in the language of media and, for more than two decades now, in that of the Internet. Reading thoroughly through such texts reveal some typical strategies of communication. The main strategies of self-identification of the Northern Irish are the strategy of self-presentation, the strategy of discreditation, and the strategy of argumentation. They all depend on the aforementioned contradictions and difficulties of Northern Ireland being a border nation between the Irish Republic and the rest of Great Britain, which means that the strategies in question are historically conditioned.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.011 |
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".