The physiological and psychological effects of windows, daylight, and view at home: review and research agenda
Bibliographic record
Abstract
A 2004 CIE report introduced the concept of a necessary daily light dose that contemporary life in industrialized countries does not deliver, but to which better use of architectural daylighting could make a valuable contribution. Nearly a decade has passed since the last substantive reviews of the health and well-being effects of daylight and windows, making it time for a renewed examination of the literature. Moreover, there has been scant attention paid to the role of daylight in residential buildings, which is the focus here. This review identified three broad processes through which residential windows and skylights can affect people in their homes, for good and ill: visual processes, acting primarily through light detected at the retina by rods and cones; non-visual ocular processes, acting primarily through light detected at the retina by intrinsically photoreceptive retinal ganglion cells; and processes occurring in the skin. This qualitative review revealed that there is no shortage of research questions facing photobiologists, psychologists, architects, lighting designers and others in the broad lighting community, whether their interests are general or specific to daylighting for residences. The report includes a detailed research agenda aimed at furthering the use of daylighting and windows in the service of human well-being.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".