In search of a climate change signal in Nova Scotia: the Alexander Mackay data, 1901-1923
Bibliographic record
Abstract
Our objective in this work is to model First Appearance Time (FAT) of flowering in five species of plants in Nova Scotia, Canada, as a function of climatic variables (such as temperatures) and geographical factors (such as latitude). Dr. Alexander H. MacKay was the superintendent of public schools in Nova Scotia from 1891-1926. Beginning in 1896 MacKay instructed all the school teachers of Nova Scotia to have their students collect data on the first appearances of numerous plants, animals, and seasonal events, and then summarized the data himself. The summaries of the phenological data collected in this massive citizen science project were then published in the Proceedings of the Nova Scotian Institute of Science in a consistent fashion over the period 1901-1923. We analyze five species from the summary MacKay data for Nova Scotia, producing a model for First Appearance Time of flowering for each, as a function of latitude, longitude, mean monthly temperatures for many months, and sea ice off the coast of Newfoundland in winter months. Our model produces good agreement between predicted FATs and those FATs we find in the literature.Key Words: 1901-1923, Alexander MacKay, First Appearance Time (FAT), flowering, latitude, longitude, mean monthly temperatures, Nova Scotia, sea ice.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".