Sėkmingos Europos komunikacijos link: studijų atradimai ir žiniasklaidos polikos rekomendacijos
Bibliographic record
Abstract
In the context of media developments world-wide including convergence of media system, journalism homogenization, diversification of political communication, it is important to understand how these processes will affect (trans)formation of the European public sphere. There has been no European news agenda across media in Europe so far, except for rare cases when European Union becomes an issue of top importance across Europe. Most often these are sensational events, crises or official meetings of the EU representatives. On the other hand, journalists are confronted with their audience, which is poorly informed and has inadequate knowledge about the EU. The aim of the article is to reassess the major challenges of European social imaginary by addressing key measures to be taken to communicate Europe effectively.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".