Where Are You Really From?: A Commentary on Ancestral Black Nova Scotian Identity
Bibliographic record
Abstract
The purpose of this commentary is to discuss Ancestral Black Nova Scotian (ABNS) identity, while advocating for the unified advancement of people of African descent (PAD) in Nova Scotia that is inclusive of ABNSs as a distinct people. I began critically examining identity and contemplating this issue during my doctoral research. As a Black feminist scholar, I have conducted reviews of literature related to PAD in Canada as well as in-depth qualitative research with ABNS nurses. My expertise on this matter is further informed by lived experience and ongoing discussions on intersectionality and Black health with mentors from across the diaspora. The sum of this insight has brought me to a change in the language that I use to describe ABNSs. I was inspired to share this commentary, at this time, for two reasons. The first—and more practical—reason involves my deepening understanding of language and identity and how I apply it in my work. The second—and more political and contentious—reason relates to the attempted erasure of ABNS identity. My position in this commentary is that of an advocate for ABNS identity alongside the unity of PAD in Nova Scotia. I acknowledge the extensive entanglement of identity with other important and multi-faceted issues, such as resource allocation; however, it is critical that these issues are understood as interconnected rather than conflated. For example, resource allocation has become so entangled with identity that the erasure of ABNS identity has become a symbolic master key to unlocking a metaphoric treasure chest. The differences that exist among PAD in Nova Scotia have created a welcomed shift in the demographic composition of the population. These shifts and unique differences mean that PAD in Nova Scotia are not a monolith, and this achievement is one to be acknowledged, celebrated, and embraced.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.038 | 0.019 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.014 | 0.023 |
| Insufficient payload (model declined to judge) | 0.003 | 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".