HCI and environmental public policy : opportunities for engagement
Bibliographic record
Abstract
This note discusses opportunities for the HCI community to engage with environmental public policy. It draws on insights and observations made during the primary author’s recent work for a policy unit at Global Affairs Canada, which is a federal ministry of the Government of Canada. During that work, the primary author identified several domains of environmental public policy that are of direct relevance to the HCI commu- nity. This note contributes a preliminary discussion of how, why, with whom, and in what capacity HCI researchers and practitioners might engage with three types of environmental public policy: climate change, waste electrical and electronic equipment, and green ICT procurement policies. This builds on existing public policy and environmental knowledge within the HCI community and responds directly to calls from some members to engage with environmental public policy.
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.
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 | 0.087 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.025 | 0.077 |
| Scholarly communication | 0.053 | 0.052 |
| Open science | 0.004 | 0.051 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".