CHA Annual Meeting / Réunion annuelle de la SHC
Bibliographic record
Abstract
Enseigner et captiver l’attention des nouvelles générations, c’est dorénavant faire appel à toute une série de savoirs qui se\ncomplètent et apparaissent inter reliés. Jusqu’à quel point faut-il repenser l’interdisciplinarité et innover dans notre approche de l’histoire ?Quel est le futur de l’histoire dans unmonde de plus en plus décloisonné et changeant ? Quelles lignes de force notre discipline est-elle susceptible d’adopter dans le contexte des nouvelles technologies ? Voici quelques-unes des interrogations que les congressistes auront l’occasion d’approfondir lors de la rencontre annuelle de la SHC en juin prochain à Ottawa. Le comité de programme 2015 a réuni pour vous sur trois jours près de 130 panels et table rondes, dont une grande partie s’intéresse à\nce thème crucial pour notre profession.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.162 | 0.057 |
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".