Canadian Humanities Computing and Emerging Mind Technologies
Bibliographic record
Abstract
The computer-assisted tools, methodologies, and structures that capture the ways in which those in the arts and humanities carry out the practices associated with their disciplines -humanities "mind technologies," as coined by the contributors to Alternative Wor(l)ds: The Humanities in 2010 1 -have been increasingly foregrounded by the academic community in recent years.Such foregrounding has been driven by many factors: the increasing computerization of our knowledge-based society; the disciplinary acceptance of the intuitive tools utilized by the society it reflects and serves; a rising understanding of the ways in which computing can serve the ongoing mission of arts and humanities research, teaching, and training; and well beyond.This volume, Mind Technologies: Humanities Computing and the Canadian Academic Community, rises out of such concerns.It is the first volume to document one important subset of the internationally significant work of the Canadian academic community in its application of computing technology to the disciplinary activities of the arts and humanities.Its points of origin are manifold, the mostCreated in 2004, NT2 regroups a dozen researchers from various universities, mainly from Quebec, under the direction of Bertrand Gervais (UQAM).Its research fields are the hypertextual creation, the migration and formatting of text on the computer screen, and the new dimensions of the imagination process fostered by the digital wave. The Mind Technologies Presentation Group• William Barker (Memorial U), What Are We Looking For in an Electronic Text? • Michael Best (U Victoria), Forswearing Thin Potations: The Creation of Rich Texts Online • John Bonnett (NRC), Changing Hieroglyphics to Cuneiform, and 3D Space to Coherent Space: The 3D Virtual Buildings Project • Susan Brown (U Guelph), Between Markup and Delivery; or, Tomorrow's Electronic Text Today • Alan Burk (U New Brunswick), The Electronic Text Centre at the University of New Brunswick • Martine Cardin (U Laval), RETREAUVQ: A Context-based Approach for Archival Finding Aids • James Chartrand (McMaster U), Bertrand Russell on the Web • Charlie Clarke
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.063 | 0.008 |
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".