Principles of healthy lighting: highlights of CIE TC 6-11's forthcoming report
Bibliographic record
Abstract
In the late 1990s, CIE began to shift its emphasis from lighting for visibility to a more broad definition of lighting quality, encompassing human needs, architectural integration, and economic constraints (including energy) [41]. Human needs, as defined here, include lighting that is appropriate to maintain good health, as well as lighting for visibility, task performance, interpersonal communication, and aesthetic appreciation.Among other developments, this definition reflects the many demonstrations that there are nonvisual, systemic effects of light in humans. Specifically, controlled laboratory and clinical studies have demonstrated that light processed through the eye can influence human physiology, mood and behaviour. These findings may provide the basis for major changes in future architectural lighting strategies.The report of CIE TC 6-11 summarises the literature in this rapidly-developing area through December 2001, including the neurophysiology, neuroanatomy, behavioural effects of daytime and night-time effects of light exposure in healthy people, and therapeutic effects of light. The report concludes with preliminary guidance concerning healthy lighting and how it might be applied architecturally. This presentation will focus on the possible architectural applications of this area of research, for lighting interiors occupied by day and by night, as a step towards lighting recommendations that respect the broadest definition of lighting quality.
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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 | 0.015 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.012 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".