2. New Media and Old Problems: Restoring Humanity in the Maryland Loyalism Project
Bibliographic record
Abstract
Following the American Revolution, Loyalist refugees lined up in New York, London, and Halifax, Nova Scotia, to share their experience of upheaval in the hope that the British state would recognize their political allegiance and compensate them for their losses through evacuation, land, a pension, or reimbursement.The state recorded the narratives of this refugee population, one of the eighteenthcentury Atlantic's largest, in two series of documents: the Inspection Roll of Negroes (known also as the Book of Negroes) and the papers of the parliamentary Loyalist Claims Commission (LCC).Both serve to establish the political allegiance and right to confiscated property of women and men who supported the Crown during a civil war, in the face of betrayal, persecution, and loss of family and friends.They are filled with firsthand accounts of wartime experiences, biographical details, and evidence of networks and geographic movements of a displaced people.Nearly 250 years later, the Maryland Loyalism Project engages undergraduate and graduate students to use digital platforms to make these poignant stories and revealing data available to scholarly and descendant communities.1 Scholars have long used these sources, but too often independently of each other, focused either on the experience of white Loyalism or Black self-emancipation. 2 Rarely is the history of Loyalism multihued.3 In telling this broader history, a guiding principle is to document while not reproducing the inhumanity often embedded in the construction and content of these historical records.Even as white Loyalists emphasized their suffering and the inhumanity of American rebels, they submitted financial claims that chronicled their own denial of humanity to enslaved women
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.035 | 0.014 |
| Scholarly communication | 0.020 | 0.009 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 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".