The Institutionalization of Deceptive Sales in Life Insurance
Bibliographic record
Abstract
Interview and ethnographic data are used to show how deceptive sales practices are rife and institutionalized in the life insurance industry. The data are analysed using the concept of ‘moral risk’: the paradoxical tendency of the structure and culture of the insurance institution to facilitate and encourage risky behaviour on behalf of the various players in the insurance relationship, in this case behaviour by insurance companies and their agents that puts consumers at risk through deceptive selling. We give empirical evidence of five key sources of moral risk that are part of the enduring structure and culture of life insurance sales. Although moral risk has been pervasive in life insurance sales since the birth of the industry, it articulates with key contemporary social tendencies: the responsibilization of the individual consumer, the erosion of the social safety net, fragmentation, individualism and the attenuation of family ties, the growth of a ‘flexible’ labour force, and the downloading of regulatory responsibility from the state. Deceptive sales practices corrode trust and promote yet more individualism, erasing the potential of insurance as a mechanism of social solidarity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".