Jezično planiranje u odnosu na malu jezičnu zajednicu (primjer italofone jezične zajednice u zapadnoj Slavoniji)
Bibliographic record
Abstract
Almost a quarter of a century ago, in 1992, Michael Kraus affirmed that a language should not fear for its future, i. e. won’t be extinguished, if it is spoken by at least 100 000 speakers. However, this statement failed to be reliable since there have been languages spoken by hardly 100 000 people that have not been endangered as well as those whose future is insecure and even at risk despite a million of its speakers. The Italian communities situated in western Slavonia, and in particular on the territory of three small towns, Lipik, Kutina, and Pakrac, represent one of those highly endangered linguistic enclaves. This paper aims to detect reasons that endanger the Italian speaking communities in western Slavonia, since other Italian communities in Croatia do not face the same situation. I start from the assumption that within the existing legal acts and institutionalised activities, there have been recesses concerning acquisition planning, unexploited so far, that could slow down the process of vanishing of this Italian enclave, or that could help it to preserve its cultural identity.
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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 | 0.002 | 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 | 0.004 | 0.011 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".