Attitudes of potential customers towards life insurance service in case of Meden Corporation, Addis Ababa Merkato branch
Bibliographic record
Abstract
This study paper was measured attitudes of Potential Customers towards Life Insurance Service in case of Meden Corporation Addis Ababa merkato brach. This study was mainly focused on factors that affect people's attitude on life insurance service, Meden Corporation in case of Addis Ababa merkato branch. The study regarding data requires collecting reliable information regarding attitudes of potential customers towards life insurance services; data collected from both primary and secondary data sources. The primary data was collected from potential customers of life insurance service in Meden Corporation Addis Ababa merkato branch by using structured questionnaire, observation. Regarding secondary data, it was collected from different documents, different web-sites, other related research works and review of journals and both published and unpublished earlier research works by the corporation, the national bank of Ethiopia and annual reports of the corporation. The data analysed and interpreted by using both qualitative and quantitative techniques which includes descriptive statistics, percentages and used tables. The study showed that most of the attitudes of the potential customers not positive, role of insurance corporations to motivate the potential customers to buy life insurance service, was very low and Promotional and public awareness creation activities were not well done. Therefore the responsible body; like life insurance corporations, government bodies, Medias, and others related businesses must carried out essential works to change potential customers' negative attitude to positive attitude, Product and the premiums charged should recognize the needs and economic status of the society and the insurance should ensure proper sales promotion and pricing of life insurance products for value maximization for its customers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".