Considering passenger pigeon abundance and distribution in the Late Woodland zooarchaeological record of southern Ontario, Canada
Bibliographic record
Abstract
Abstract The passenger pigeon (Ectopistes migratorius) was once the most abundant bird species in North America. Flocks of these birds witnessed in the early 19th century were so vast that they were said to darken the sky for days as they passed. Early syntheses of passenger pigeon remains in archaeological contexts in the eastern United States, in contrast, found them to be relatively rare in relation to other fowl, leading to the suggestion that the colonial‐era hyper‐abundance of passenger pigeons was a post‐European‐contact phenomenon resulting from contact‐induced demographic and ecological changes. In this paper, we provide new insights into passenger pigeon historical ecology through a synthesis and GIS‐based analysis of zooarchaeological data on skeletal remains from 157 Late Woodland (ca. 900–1650 CE) sites in Ontario, Canada. Our results reveal that passenger pigeon bones are common, and often abundant, in Late Woodland archaeological assemblages in Ontario, which speaks to the species' importance to Indigenous peoples in the region. However, the relative abundance of passenger pigeon remains varies over time, suggesting longer‐term trends in their availability and/or in hunting patterns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".