History, Interactive Technology and Pedagogy: Past Successes and Future Directions
Bibliographic record
Abstract
Based on a keynote presentation at the 2012 Canadian Historical Association conference, this paper surveys the state of digital technology and its impact on academic publication and teaching in the contemporary university. Focusing on the dramatic rise of the Digital Humanities in the last few years, the paper examines alternative forms of peer review, academic scholarship and publication, and classroom teaching as they have been reshaped by the adoption of a variety of digital technologies and formats, including open-access, online peer reviewing, use of databases and visualization techniques in humanities work, online journal publication, and the use of blogs and wikis as teaching tools. Examining the digital production and education work of the American Social History Project at CUNY, which he co-founded, and the Interactive Technology and Pedagogy doctoral certificate program that he heads at the CUNY Graduate Center, the author discusses a range of digital projects and approaches designed to improve the quality of teaching and learning in college classrooms.
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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".