Imported Toponymy and the FamilySearch Place Name Database: Mapping North American Communities with European Capital Namesakes
Bibliographic record
Abstract
Place names lend themselves very easily to cartographic and geographic research, and they have been studied extensively from these perspectives. Recent technological advances have allowed for a more rapid geographical study of toponyms of many types. An additional, albeit less visible resource with a robust place name system is the FamilySearch genealogical database. FamilySearch is the world leader in open-source genealogical data and hosts a user-contributed family tree that contains more than one billion names. In this article, the authors explore how the FamilySearch genealogical database likewise offers a user-contributed dimension for analysing and mapping place names. They then use the filter functions of the FamilySearch place database tool to map the spatial diffusion of 438 communities across Canada and the United States that share the names of European capitals. The authors find that these North American “imported capitals” provide evidence of local connections to larger-world happenings, thus broadening the implications of Wilbur Zelinsky’s 1967 theory to include the significance of not only Greco-Roman values but Europeanness as well.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".