Lighting for well-being: a revolution in lighting?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A model of lighting quality proposed in the 1990s defined good lighting as that which balances the needs of humans, economic and environmental issues, and architectural design. The model made explicit what had long been implicit: Lighting is not just about seeing details. Good lighting provides for the needed level of visual performance, but also determines spatial appearance, provides for safety, and contributes to human health and well-being. Far from being a revolutionary proposal, lighting for everyday well-being has long been a goal of lighting recommendations. The question for today is how quickly we should incorporate new research findings in revisions of recommendations. This paper will address the knowledge base and the state of lighting recommendations for three aspects of interior lighting that contribute to health and well-being: areas of high luminance (about which much is known, but more to be learned); luminous modulation (flicker) (about which we have some knowledge); and, total daily light exposure (about which knowledge is weak, but suggestive). Appropriately, recommendations are most specific for those areas about which knowledge is strongest. Revisions should keep pace with evolving knowledge, but not run ahead.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it