He’s ours, not yours! Reinterpreting national identity in a post-socialist context
Bibliographic record
Abstract
This paper focuses on the relationship between sport, national identity and the media in the post-socialist nation-states of Croatia and Slovenia. It describes what has changed during the eight years since Jakov Fak, a Croatian-born Slovenian biathlete, changed his citizenship and began competing for the Slovenian national team. It also examines how the perception of Jakov Fak as an athlete and of his success has changed through time in different socio-political circumstances – in 2009 and 2010 when he competed for Croatia, and after 2010 when he began competing for Slovenia. To analyse this case we have used different media interpretations of Jakov Fak case, analysing four sports events: the Biathlon World Championships in South Korea (13–22 Feb 2009) and Germany (1–11 Mar 2012), and the Olympic Games in Canada (11–18 Feb 2010) and South Korea (9–25 Feb 2018). The results of discourse analysis show that in the case of Jakov Fak in the years 2009 and 2010, the public was provoked by and exposed to national symbolism, especially in political discourse. The media discourse did change between 2012 and 2018, and discourse typical of civic nationalism began to dominate. Two types of nationalism are mixed in a post-socialist context.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".