Thermal comfort in lower economic groups: The applicability of the ASHRAE-55 adaptive standards in informal settlements and refugee camps
Bibliographic record
Abstract
Thermal comfort is influenced by climate, expectations and adaptation opportunities. Hence the emergence of adaptive thermal comfort standards. Unfortunately, international adaptive standards and much of the underlying literature, are based on data collected from middle-income individuals in office or apartment blocks, raising the question of their validity in other contexts. This paper is the first large-scale investigation of the applicability of these standards to populations living in refugee/displacement camps, to establish whether comfort theory needs to be modified for such populations. This was achieved through highly difficult, data collection in camps in Jordan, Djibouti, Ethiopia and Peru. The data collected consists of 1982 rows of personal variables and concurrent environmental measurements. From these, the thermal comfort boundaries of the displaced were found to be wider (13K) than suggested in prevalent standards (8K). A new mathematical model of thermal comfort for such groups is hence developed. The results expand our understanding of comfort theory to include an understudied population and will be useful for those responsible for shelter for the currently 120M displaced, as they now allow rational design standards to be set. A tool based on the new model is currently being applied by aid agencies in camps in Afghanistan. Practical Application The design of refugee accommodation across aid agencies requires the setting of design standards, as these impact material choice, construction techniques and cost, and hence the number of people that can be housed in any disaster. Highly constraining standards can thus reduce the population that can be housed, with associated implications for mortality rates. The alternative being the failure to set any quantitative target, creating a danger to life. The new thermal comfort model presented here allows for the first time the setting of targeted comfort design standards in camps.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".