Bibliographic record
Abstract
The new Trudeau government has made a tonal shift in Canada’s international development policies. However, not unlike many governments in the overdeveloped world, Canadian policies are still used to export and embed neoliberal rationales perpetuating global inequalities that development policies are supposed to right. Mah and Rivers suggest how design and social science, together, can advance a more progressive international development agenda. They do this by highlighting their ongoing Democratic Crèche project. This sustainable development project entails the prototyping of two early childhood development (ECD) centres, or daycare centres, in South African townships. Beyond the realization of physical structures that enhance children’s wellbeing, the project ultimately demonstrates the difference made when social design is used “to do” and “to study” development in alternative and critically engaged ways. “Alternative” and “critical,” here, necessitate development policies and projects emanating as much from townships as Global North capitals. About the Lecturers: Kai Wood Mah is a registered architect, design historian, and professor. Patrick Lynn Rivers is a political scientist and professor at a leading school of art and design. Together, they co-direct Afield, a design research practice bringing comparative interdisciplinary perspective to contemporary social issues.
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 | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.027 | 0.007 |
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".