‘Heritage from Below’: Building and Developing The South Asian Canadian Digital Archive (SACDA)
Bibliographic record
Abstract
Abstract - Post-Custodial Stewardship: Creating a South Asian Canadian Digital Archive Through Community Partnerships The history of the South Asian Canadian diaspora can be seen in select holdings across dozens of repositories in almost every province in Canada. Unfortunately, the holdings of these repositories are relatively few and represent the stark undercollection of South Asian diasporic history by Canadian memory institutions. There are no fonds or collections for several significant South Asian organizations or collectives, like the Ghadar Party. Primary sources for important historic events like the Komagata Maru tragedy are heavily stratified across several archives. The forthcoming South Asian Canadian Digital Archive (SACDA) aims to rectify this inequity by using a post-custodial model to unify the private and public holdings of archives, museums, individuals, families, and organizations through a publicly accessible digital repository. This presentation will discuss the archival gaps for South Asian Canadians and how SACDA’s model for loans and acquisitions aims to fill those gaps, as well as how SACDA is approaching metadata, digital preservation, and asset management using open source tools to better serve community stakeholders. SACDA is being built on the software suite Collective Access and preserved using Archivematica in addition to other open source scripts and tools. Abstract - Threading Social Justice Perseverance into the Archive The SACDA model’s success is built on the idea of “heritage from below” where the construction of the archive is fuelled by leaning heavily on personal narratives, collections and artefacts. The limited source of organizational support has forced a keen and sharp analysis of lived experiences for a young settler community in Canada (est. 1903). South Asian Canadian responses to social justice and activism has created a rich and vibrant storehouse of knowledge that hitherto has remained locked up in the memory/collection of its subjects. A new and inclusive archive that documents the real injustices and the ensuing resilience/response/activism to the trauma (mostly racially motivated) will be well documented for future generations. The exclusion of their resilience is a grave omission in the Canadian record that needs to be (re)collected and (re)informed.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".