‘She of the Loghouse Nest’: gendering historical ecological reconstructions in Northern Ontario
Bibliographic record
Abstract
This paper brings together feminist historical geography with historical ecology as a means to integrate “gender” as a category of analysis when conducting historical ecological reconstructions . Northern Ontario’s ecological past can be discovered in the vast natural history collections housed in museums across North America and the United Kingdom. Natural history specimens reveal important scientific information about past habitats, climates, and ranges and distributions of species. However, while such cumulative data have been crucial to works in historical ecological reconstructions, the ways in which such gendered knowledge has been produced and circulated remains under studied. In 1927, Swedish immigrant Louise de Kiriline Lawrence (1894-1992) settled on Pimisi Bay, Ontario, and became an authority on the breeding behaviours and ranges of several northern Ontario bird species. Material remnants of her contributions exist as records, bird skins, and nests in the Canadian Museum of Nature in Ottawa and the Royal Ontario Museum in Toronto, as well as in professional ornithological publications. As this paper demonstrates, de Kiriline Lawrence gained authority in “the field” through the domestic sphere of her “ Loghouse Nest” home . Her expertise included the breeding behaviours of birds, such as courtship, nesting habits, and rearing of the young , areas deemed suitable for women in the first half of the twentieth century . De Kiriline Lawrence’s natural history specimens , therefore, can also be conceptualized as cultural artefacts reflective of gendered situated knowledges , an importan t consideration when engaging in critical historical ecological reconstructions of past environments.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".