An Empire on Paper: The Founding of Halifax and Conceptions of Imperial Space, 1744–55
Bibliographic record
Abstract
The founding of Halifax in 1749 was a watershed in British imperial policy. The settlement was state-funded and served political, not commercial, aims. Mapping – the creation and representation of geographic knowledge – was essential to Halifax's success because it shaped Britain's relationship to the land and subsequently influenced how Britons in the settlement interacted with each other and with resistant groups. Cartographic knowledge was never static, but instead was affected by cultural, political, and economic realities that directed the work of local commissioned surveyors like Charles Morris, and metropolitan public mapmakers like Thomas Jefferys. From 1744 to 1755, geographic imaginings of Halifax changed to address specific imperial goals: first, reconnaissance maps and surveys delimited boundaries and provided data; second, early settlement geographic knowledge established Britain's claim to the Halifax region by controlling the Native presence and emphasizing British strength; and third, ‘popular’ cartography rallied support for the empire by promoting attractive imperial images among Britons. Geographic knowledge produced from the Halifax settlement indicates that spatial information was Janus-faced: maps and reports negotiated a fine line between value-free geographic information and imperially favourable geographic imaginations. In each case mapping and its cartographic evidence were key independent variables in the socio-political organization of power that situated early modern Canada in a British Atlantic world.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".