Bibliographic record
Abstract
Within many archives and library special collections, genealogical researchers make up the largest user group. Most studies show that in North America and Europe, they can account for fifty to ninety percent of all users. The paper addresses the historical background of genealogy within our reading rooms and an expanding world of family history via archival and library websites, examining family history as presented on selected websites of archives and libraries in the United States, Canada, England, and Scotland. A website analysis focused on three main objectives: to establish the current state of our most public face presented to genealogical researchers; to identify current areas of best practice and those which require improvement; and to form a vision of what archives could offer on websites to family historians. RÉSUMÉDans plusieurs collections spéciales des centres d’archives et des bibliothèques, les chercheurs généalogistes constituent le plus grand groupe d’usagers. La plupart des études concluent qu’en Amérique du Nord et en Europe, ils peuvent compter pour environ 50 à 90 p.c. de toute la clientèle. Ce texte considère les antécédents historiques de la généalogie dans nos salles de consultation ainsi que le domaine de l’histoire familiale par le biais des sites Web des archives et des bibliothèques, en examinant l’histoire familiale telle qu’elle est présentée sur divers sites Web des archives et des bibliothèques aux États-Unis, au Canada, en Angleterre et en Écosse. Cette analyse des sites Web vise trois cibles principales : établir l’état actuel de nos vitrines publiques telles qu’elles sont présentées aux chercheurs généalogistes, identifier les domaines de pratiques exemplaires ainsi que ceux qui requièrent de l’amélioration et créer une vision de ce que les archives pourraient offrir aux généalogistes sur leurs sites Web.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.134 | 0.014 |
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".