Prospective ergonomics for the design of future things
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
This position paper gives an overview of the field of Prospective Ergonomics (PE) for the design of future products, services, processes, and systems. It presents its definition, links with innovation, characteristics, origin, history, goal, supports, and methods to help people imagine the future. In recent years, PE has been rediscovered, actualised and repositioned to give it greater scope and visibility, and stimulate research, training and professional practice in ergonomics for the design of future things. PE is an ergonomic intervention mode, on a par with Corrective ergonomics and Design ergonomics, upstream of design projects, where the ergonomist is proactive in anticipating or constructing future user needs and in creating future artefacts. PE is supported by four main fields of study: Ergonomics, Prospective, Future-Oriented Cognition, and Creativity, which ensures it is guided by three key principles: human-centred, future-oriented, and focused on creativity for innovation. PE expands the scope of ergonomics by going beyond the design of interactions with artefacts and including the creation of these artefacts in the first place. This has major impacts on research, training, and professional practice in ergonomics because we need new knowledge to work efficiently on the future, training should be enhanced in prospective, innovation, and new product development, and the professional practice is enriched by a new set of activities. In the conclusion we propose future research directions to pursue the development of PE.
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 | 0.001 |
| 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