Travel, Displacement, Place, and Identity: Exploring archival stories through Digital Humanities and Social Sciences curriculum
Bibliographic record
Abstract
Like curriculum, archives can limit or expand knowledge. They hold the promise to maintain or to challenge norms, values, and beliefs of dominant society through their creation and use. They can be the ends as well as the means of teaching and learning. Also like curriculum, situating archives with digital technologies can hold the promise of different ways to understanding and interpreting the world. With these links to guide, this paper will demonstrate the ways in which archival resources can expand curriculum and pedagogy when used under the umbrella of Digital Humanities and Social Sciences. Drawing on a collaborative project undertaken by administration, library, and faculty at a large university in Canada, this paper will demonstrate the pedagogical and curricular possibilities for telling archival stories under the theme(s) of travel, displacement, place, and identity using DHSS tools, technologies, and pedagogies. By sharing the results of this project, this paper will highlight the curricular possibilities needed to critically and actively engage in experiential and e-learning in the humanities and social sciences and the ways in which curriculum can be expanded and challenged by the digital and archival.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| 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 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".