Bibliographic record
Abstract
This is the final report of the British Columbia component of research that was conducted by the BC-Alberta Social Economy Research Alliance (BALTA), the Alberta Community and Co-operative Association (ACCA) and the British Columbia Co-operative Association (BCCA) on survival rates for newly incorporated co-operatives in both provinces and factors which influenced survival. The research found that co-ops experience significantly higher survival rates than other forms of business start-ups. The 5-year survival rate in B.C. was 66.6%. By contrast, Industry Canada figures show a 43% and 39% 5-year survival rate for conventional business start-ups in 1984 and 1993 respectively. In BC, business start-ups in 1984 experienced a 38% 5-year survival rate. Successful co-ops identified the following factors as being key to their development and survival: \n• Acquisition of capital & strong financial planning & management \n• Member engagement & board involvement & expertise \n• Training & enlisting outside consultant expertise and support \n• Business planning and clarity of purpose. The report includes recommendations for ways to enhance support to co-operative development and survival.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".