Participatory Design Methods of the Displaced
Bibliographic record
Abstract
The primary question guiding this research is: How might social service agencies create viable organizational cultures of innovation? This research looks at recent innovation design experiences of social service organizations in Toronto. It describes the context in which these projects are pursued and acknowledges some of the current criticisms of an emerging social innovation industry. \n \nThis research is exploratory and proposes perspectives for an agency-driven framework for innovation work. These perspectives are rooted in concepts from three fields of study and practice—Systems Thinking, Participatory Design and \nTraditional Knowledge. \n \nCreative outcomes of this research look to contribute to \nenvisioning an Indigenizing approach to participatory design. One that acknowledges, engages and empowers some of the \nmost resilient, innovative and resourceful—yet displaced \nindividuals—in co-creating social programs and services \nas well as imagining possible futures.
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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 | 0.084 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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".