Climate, climate change and the global diversity of human houses
Bibliographic record
Abstract
Globally, human house types are diverse, varying in shape, size, roof type, building materials, arrangement, decoration and many other features. Here we offer the first rigorous, global evaluation of the factors that influence the construction of traditional (vernacular) houses. We apply macroecological approaches to analyse data describing house features from 1900 to 1950 across 1000 societies. Geographic, social and linguistic descriptors for each society were used to test the extent to which key architectural features may be explained by the biophysical environment, social traits, house features of neighbouring societies or cultural history. We find strong evidence that some aspects of the climate shape house architecture, including floor height, wall material and roof shape. Other features, particularly ground plan, appear to also be influenced by social attributes of societies, such as whether a society is nomadic, polygynous or politically complex. Additional variation in all house features was predicted both by the practices of neighouring societies and by a society's language family. Collectively, the findings from our analyses suggest those conditions under which traditional houses offer solutions to architects seeking to reimagine houses in light of warmer, wetter or more variable climates.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".