Who Are We Listening to? The Inclusion of Other-than-human Participants in Design
Bibliographic record
Abstract
Designers' considerations of whom to include as a participant in design research continue to broaden, listening to individuals and communities previously unheard. Some even argue that other-thanhuman entities should be recognized as a type of participant, advocating for non-humans to have a voice in the design process. Through this paper we contribute to this conversation, arguing for a remembering of how to attend to our interactions with diverse forms of life. We refer to these entities as 'pervasive peripheral participants', drawing on early scholarship of Jean Lave and Etienne Wenger. We use this provocative phrase deliberately, to prompt us to consider how we learn with and through these relationships. Non-human, peripheral participants are ubiquitous in all aspects of life, and may inspire designers throughout their project's lifetime, from the environments in which they work, to the resources they use. These participants implicate and are implicated through design. While we recognize that the inclusion of pervasive peripheral participants in design processes is a challenging step to take, this paper holds up scholarly contributions which offer insights to those willing to join this work. We look to projects that do not limit participation in design to human-centred perspectives. These projects offer examples of how to engage with other-than-human ways of being, responding to Daniel Heath Justice's call to "imagine otherwise" (danielheathjustice.com). Learning from these approaches, we imagine how we might attend to relations with otherthan-humans through relinquishing control, fostering collaboration and relationality, practicing reciprocal acts of care, and valuing other temporalities. In doing so, we envision a future when interaction design practice welcomes a broader array of participation, creating space for more ethical and diverse worlds.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".