Developing Academic Capacity in Digital Humanities: Thoughts fromthe Canadian Community
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>Despite DH&rsquo;s long history, it is still perceived as a relatively emergent academic disciplinewhich has several implications for its ongoing development and acceptance. In order tounderstand its role in supporting the field&rsquo;s development and acceptance, SSHRCcommissioned a survey of the larger Humanities and Social Science&rsquo;s community tounderstand the issues related to DH&rsquo;s development and acceptance and the types ofactivities that should be funded. The survey results suggest there is reason for optimismregarding the growing acceptance of digital methods, resources and tools and electronicdissemination as instructors, researchers, and students are using and publishing indigital outlets and creating and employing digital recourses, methods and toolsandventuring into new research fields. This trend is likely to continue as students andyounger scholars continue to embrace the digital in all aspects of their personal andprofessional lives. However, this optimism should be tempered to some extent asstudents and junior faculty are still less likely than associate professors to present andpublish their digital-oriented research for a variety of reasons. The field&rsquo;s more seniorfaculty can mentor their junior colleagues and students to this end and shape salary,tenure and promotion policies to recognize and reward these efforts. Finally, issuesremain around the amount of funding required for the initial development and ongoingsustainability and relevance of digital resources and may become more critical over time.Granting agencies will need to evaluate their funding role in this regard.</p>
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it