Insurance Perspective on Talent Management and Corporate Social Responsibility: A Case Study of Nordic Insurers
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
Insurers are facing a problem of attracting new talent. They are competing with other industries for talent while clients simultaneously demand more service from insurers. At the same time, the industry is regarded as 'un-sexy', having poor reputation, and the talent pool is limited. The aim of this paper is to explore whether corporate social responsibility/sustainability emphasis can be used to attract talent to the insurance sector. The paper is based on a multi-case study including 16 Nordic non-life insurance companies, focusing on the environmental factor of corporate social responsibility or environmental sustainability, depending on the company’s terminology. Qualitative methods were used to collect data, including 74 interviews with insurance executives and specialists. The paper suggest that focus on corporate social responsibility can be an enabling condition when attracting talent, i.e. if companies have a higher agenda than gaining more profit today than they did yesterday. Running a successful business requires companies to recognize the trends that will alter their business environment. If they incorporate and deal with issues of key concern for their future employees they are more likely to succeed in attracting talent.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it