Hutterite colonies and canopy cover: A remotely sensed analysis of the effects of cultural-religious beliefs on the treed landscape
Bibliographic record
Abstract
Located across the extent of the Canadian Prairies, the Hutterisch-speaking Hutterites are comprised of four groups or kinships: the Lehrerleut, Dariusleut, Schmiedeleut-1, and Schmiedeleut-2. Previous limited case studies have highlighted how the use of trees across the landscaped communities, including for aesthetic and agroforestry objectives, differs between the four kinships. Using photo-interpretive analysis of stratified samples using remotely sensed imagery, I examine canopy cover and the spatial distribution and composition of trees within 100 Hutterite colonies, testing the conclusions of prior case studies with limited sample sizes. The results illustrate that canopy cover around built infrastructure and aesthetic use of trees significantly differs between kinships and that a higher canopy cover is more common amongst the Schmiedeleut colonies, consistent with prior studies. The canopy cover extent differed significantly between different ecological areas; however, this is confounded by the historical immigration patterns and distinct economic ventures of the Kinships. The canopy cover extent can also be traced back through the parental linkages, which shows significant differences between parental origins. This research helps add to discourse surrounding the influence of ethnocultural values on landscaping preferences at a large scale and provides both quantitative and qualitative remotely sensed methods for socio-ecological studies with the potential to complement ethnographic interviews and surveys.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".