Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It was in 1996 that Integra1, a large Canadian life insurance institution, launched its Banking and Loan Insurance Software System (BLISS) development project with the aim of gaining access to the loan insurance market in small Credit Unions (CUs) across Canada. The company was ready to provide the system free of charge to the Credit Unions on the provision that they commercialize exclusively Integras loan insurance products. To achieve this goal, Integra entered into a partnership with Intex Consulting, the Canadian subsidiary of a large international information system (IS) integration firm who wanted to gain a foothold in the Canadian banking business. After 1.3 million dollars of investment from each partner and twelve months of intensive efforts, the project came to an abrupt stop. The lessons learned in this case study include: (1) the importance of understanding requirements beyond micro-level user needs, (2) the need to get the enlightened involvement of each interested party in a large complex project, (3) the importance of appraising the specific contribution of each partner in a strategic alliance, and (4) the obstacles faced when entering an unfamiliar market with a new, unproven IS product.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it