Digital Humanities: The Continuing Role of Serendipity in Historical Research
Bibliographic record
Abstract
The move towards the digital humanities will see a growing interest in digital tools, such as Ebooks. This study examines the opinions and perception of historians about how Ebooks and other digital tools affect the research process. Findings indicate that historians are concerned that the digital environment reduces the possibility of chance encounters with a text. They continue to recreate the environment that encourages serendipity to occur within their field, and would readily welcome tools that facilitate this.Le passage vers les humanités numériques ira en grandissant, grâce à la popularité des outils électroniques et des livres électroniques particulièrement. Cette étude examine les opinions et les perceptions des historiens quant aux livres électroniques et autres outils numériques dans le cadre de leur processus de recherche. Les résultats indiquent que les historiens se soucient du fait que l’environnement électronique puisse réduire les possibilités de découvertes fortuites dans les texte. Ils continuent de récréer un environnement qui suscite la sérendipité dans leur domaine et adopteraient volontiers un outil qui leur faciliterait la tâche à cet égard.
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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 | 0.066 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.015 | 0.087 |
| Scholarly communication | 0.032 | 0.031 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".