HCI Research on Agriculture: Competing Sociotechnical Imaginaries, Definitions, and Opportunities
Bibliographic record
Abstract
Agriculture is foundational for food security on our planet. Considering climate change and other pressures on food production, HCI scholars have increasingly begun to examine how the field should approach agricultural innovation. We conducted a literature review of HCI research through the lens of competing future visions for good food systems : a “conventional” vision of profit-oriented production, and an “alternative” which prioritizes sustainability and community-led practices. Leveraging the concept of sociotechnical imaginaries, we provide an empirical analysis of how HCI and adjacent applied computing projects align with these competing visions for agriculture. This review reveals, amongst other findings, a prioritization of the perspectives of the Global North and a need for more careful attention to the constraints and aspirations of subsistence farmers. Finally, we note the limits of the conventional-alternative binary that shapes much of contemporary HCI research focused on agriculture and offer opportunities for transcending this framing.
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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 | 0.031 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.006 | 0.059 |
| Scholarly communication | 0.028 | 0.032 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".