Comparing better building design and operation to other corporate strategies for improving organizational productivity: a review and synthesis
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
‘Better buildings’ are intended to improve employee well-being and other important organizational productivity metrics, but such effects have been notoriously difficult to quantify convincingly. This paper uses new, multi-metric approaches to develop a framework for valuing these effects. The organizational productivity metrics considered are: absenteeism, employee turnover intent, self-assessed performance, job satisfaction, health and well-being, and complaints to the facilities manager. The effects of several ways of improving building design and operation (improved ventilation, enhanced lighting conditions, green building certification measures) are compared to the effects of other corporate strategies also employed with the intent of influencing employees to improve organizational productivity: office type (private vs open-plan), workplace health programs, bonuses, and flexible work options. Results were derived from a broad search and synthesis of published information from several disciplines: business, medicine, psychology, engineering, and facilities management. The scope was limited to studies conducted in real organizations in large office buildings, with a geographic focus on studies from North America, Europe, and Australia/New Zealand. In summary, better buildings strategies provided benefits on multiple organizational productivity metrics at levels similar to other corporate strategies. This supports greater consideration being given to better buildings strategies to improve organizational productivity beyond energy savings. In this paper, and for want of more primary research, the ‘better buildings’ category blends the effects of different improvements; this synthesis is proposed as a starting point to encourage more buildings research in this context, allowing future differentiation of the effects of specific interventions.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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