Digital Oral Histories for Reconciliation: The Nova Scotia Home for Colored Children History Education Initiative (DOHR)
Bibliographic record
Abstract
Digital Oral Histories for Reconciliation (DOHR) is a history education initiative to teach Grade 11 students about the Nova Scotia Home for Colored Children (NSHCC). The NSHCC, opened in 1921, was a segregated welfare institution for African Nova Scotian children. Residents suffered the effects of institutionalized racism in the Home throughout its 70 years. DOHR has partnered in the educational mandate of the restorative inquiry into the Home to co-design with the former residents a curriculum about their experiences (Province of Nova Scotia, 2015, p. 26). The purpose of the DOHR curriculum is for former residents to share their oral histories to develop students’ historical consciousness about institutionalized racism and to build right relations in their communities. The project was piloted in two Halifax area schools in October 2019. This symposium introduces attendees to the curriculum and shares initial findings from the pilot. Former residents share their impetus for the project, while other DOHR members share findings about the use of oral history—first person accounts of lived experiences with the past—as a restorative approach to redress of harms in education (e.g., Llewellyn & Llewellyn, 2015); how historical thinking lessons develop students’ historical consciousness—their sense-making of the past for orienting themselves to the present and future (Seixas 2004); and how DOHR’s use of virtual reality supports reconciliation with pedagogy-led (rather than technology-led) design principles (Kwon, 2019). To our knowledge, this is the first history education project centred on first-voice, to address reconciliation for African Nova Scotians.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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".