Bibliographic record
Abstract
Many social economy organizations either operate out of, or own and manage, heritage buildings in urban and rural places. These heritage buildings provide a variety of functions from the provision of affordable housing and safe-houses to artist co-operatives and studio space for cultural groups. Others house social and human services organizations, treatment centres, retail co-operatives and office space for the non-profit sector. In the provinces of Alberta and British Columbia, Canada, the stories of these buildings reveal existing or potential alliances between social economy activists and social and heritage preservation entrepreneurs. As Canada moves towards a national municipal heritage program, we analyzed the dialogue around heritage, social economy and the built environment – that is, the innovative and well-considered use or adaptive re-use of heritage architecture not only in terms of social economy assets or the sustainability benefits of reuse and embedded energy, but also in terms of conserving a ‘built heritage’ of social democracy in the contemporary urban fabric, an architecture of the social commons and social solidarity. We explored links between heritage preservation policy and the funding and operations of the social economy sector. Several cases were examined.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.027 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".