Bibliographic record
Abstract
With Assembling Understandings, the Canadian Social Economy Hub has developed a thematic summary of the CSERP outputs, exploring some of the dominant crosscutting themes within the research findings. This approach is very similar to a grounded theory approach wherein the authors, while reviewing the various available documents, ‘listened’ to the data for emerging themes. Care was taken to engage with the work from multiple angles, taking note of both diversity and unity within the body of research. The challenge in this form of research was for the authors to construct each chapter based on what was covered in the research as opposed to the expanse of what can be covered under each theme. In this way, the overall picture provided here is not a complete analysis of Canada’s social economy landscape, but rather provides an overview of the CSERP research findings in the following thematic areas: Mapping, Social Enterprise, Co-operatives, Indigenous Peoples, Organizational Governance & Capacity, Social Finance, and Public Policy. Each thematic area had representation in over 50 CSERP projects, with some chapters involving as many as 85 relevant research products. As a result, Assembling Understandings is a useful reference point for both reviewing the available CSERP documents and identifying where further research may be required.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.033 | 0.026 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.663 | 0.012 |
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; both teacher heads agree on what is shown here.
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".