A Name, A Voice, A Life: Exhibiting the Stories of 17th-19th Century Black Newporters
Bibliographic record
Abstract
“A Name, A Voice, A Life,” the NHS exhibit, was up from May until November 2024 at NHS headquarters on Touro Street. In their article about the “A Name, A Voice, A Life” exhibit, co-curators Kaela Bleho and Zoe Hume detail the vitality and resilience of Newport’s historic Black community. The lives and voices of Black residents, enslaved and free, have been notably absent from the historical record. As Bleho and Hume explain, the exhibit evolved out of a massive multi-year effort to uncover the names and lives of Newport’s Black residents, to disentangle their narratives from traditional, often biased sources, and to claim the fundamental centrality of the Black community in Newport’s history. Zoe Hume is a doctoral candidate in the Museum Education and Visitor- Centered Curation program at Florida State University. Her research interests and professional practice center activism, belonging, and difficult histories in memory work. She was a Buchanan Burnham Fellow with the NHS in 2021. Since then, she has worked closely with the staff at NHS creating biographies for the ongoing Voices From the Archives project. Kaela Bleho has worked in the museum field for over ten years, both as a digital specialist and a researcher. She joined the staff at Newport Historical Society in 2019, where she is Collections and Digital Access Manager and project lead on the Voices initiative. Kaela has a master’s degree in Archaeology from University College London (2015), and a bachelor’s in Anthropology from McGill University (2014).
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.046 | 0.029 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".