Climate Observing During Canada’s Empires, 1742–1871: People, Places and Motivations
Bibliographic record
Abstract
A wealth of pre-Confederation weather and climate observations were recorded in Canada by individuals and institutions during both the French and British empires. This scientific heritage came about for a number of reasons. For instance, the Hudson’s Bay Company wanted to reduce operating costs by having their posts in Canada’s north-west become self-sufficient in agriculture. Others wished to save lives from cholera or shipwrecks, or to satisfy curiosity about the ever-present debate concerning anthropogenic climate change. Today, historical climate observations can be found in many diverse locations. Despite our rich scientific heritage, turning archival paper and ink observations into scientific data remains an enormous technical challenge. This challenge falls to our generation, both to use this heritage to investigate the historical context of current climate change and variability, and to use the digital resources in development today to safeguard our scientific heritage for future generations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".