Past, present, and future of E/HF for sustainability: A perspective from the HFSD Technical Committee
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
BACKGROUND: Sustainability is a highly important theme worldwide and currently is being tackled by almost all disciplines. Indeed, the future of humanity is dependent on the actions taken now and in the immediate future. The Ergonomics and Human Factors (E/HF) community has not been indifferent to this issue, and one of the concrete actions adopted by the International Ergonomics Association (IEA) was the establishment of the "Human Factors for Sustainable Development" (HFSD) Technical Committee. OBJECTIVE: To identify future paths of action, this paper recognizes the trajectory of the HFSD Technical Committee, summarizes the contributions presented at IEA2021, the International Congress on Ergonomics held virtually in Vancouver in 2021, and reflects on key aspects that should be boosted by the Technical Committee. METHODS: This is a qualitative interpretative study that reflects on the contributions of members of the HFSD community working on E/HF for sustainability. RESULTS: Central topics and opportunities in E/HF and sustainability include complexity of systems, behaviors, and work; energy use and consumption; co-design, interconnectivity, territories, and the relationships with stakeholders. CONCLUSION: Although the contributions have been growing, there is still a lot of work needed, both theoretically and practically. Themes to be discussed include the concepts of sustainability and work. Considering the centrality of human beings (i.e., decision making for achieving the different dimensions of sustainability), the authors identify a set of values as core principles for leading the discussion.
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