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
For both academics and practitioners, the dominant focus of customer relationship management has been customer retention. The authors assert that customer winback should also be an important part of a customer relationship management strategy. Customer winback focuses on the reinitiation and management of relationships with customers who have lapsed or defected from a firm. In some cases, firms engage in extensive efforts to reacquire lapsed customers or defectors, and a common tactic is lowering the price to reacquire a customer. This investigation goes beyond the reacquisition pricing strategy and also examines the optimal pricing strategy when the customer has decided to reinitiate the relationship. By simultaneously modeling reacquisition and duration of the second tenure with the firm, the authors determine that the optimal pricing strategy for their application involves a low reacquisition price and higher prices when customers have been reacquired. In addition to pricing strategy, they also discuss the implications of their findings for targeting lapsed customers for reacquisition.
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 | 0.023 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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