Bibliographic record
Abstract
Abstract While the domain of toponymy has great research potential, it has so far gained little attention in Iran. The present paper is a typological study on a sample group of toponyms from two different provinces of Gilan (a northern coastal province next to the Caspian Sea) and Bushehr (a southern coastal province beside the Persian Gulf) within the framework of the Australian National Placenames Survey typology proposed by Tent and Blair. The two regions in question are similar in terms of adjacency to a major water body but different in language, culture, and geography. To determine whether the Australian proposed typology is applicable to Iranian toponyms, we collected 60 coastal placenames from Gilan and Bushehr and classified them according to their Specifics and Generics based on Tent and Blair’s ( 2009 , 2011 ) typology. Further, we compared placenaming motivations and processes in the two regions. The results show that although the Iranian placenames differ from the Australian ones in terms of their structure, they fit well into the typology. Water-related features are among the top motivations for local namers in both Gilan and Bushehr. Nevertheless, Bushehr namers are more motivated by natural features while those from Gilan, in most cases, are non-naturally motivated.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".