Normering av stadnamn: lover, forskrifter og praksis – ein analyse av saker som har nådd Klagenemnda for stadnamnsaker i perioden 2012–2022
Bibliographic record
Abstract
The Norwegian Place Name Act (lov om stadnamn) has gone through no less than three major revisions since 2005. The purpose of this study is to examine which sections of the different law texts the Appeal Board for Place Names (Klagenemnda for stadnamnsaker) has emphasized when they have made decisions about the spelling of Norwegian place names, and which trends can be identified through a study of the actual decisions made by the Appeal Board in the period 2012–2022. The study shows that the main rule in the Norwegian Place Name Act, that one should start from the inherited local pronunciation and follow the spelling principles and rules for Norwegian, has been decisive for a clear majority (67.5%) of the decisions made by the Appeal Board throughout the period. At the same time, the study shows that in around a quarter (23.9%) of the cases, the Appeal Board has made decisions about spellings that deviate from this general rule with reference to various exceptional provisions in laws and regulations. However, there is no statistical basis for claiming that the increasingly liberal legal and regulatory texts have led to an increase in the proportion of decisions on spellings that deviate from the main rule throughout the examined period.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".