The value of job security: a lower‐bound estimate from a human capital perspective
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
Purpose The purpose of this paper is to present an approach to quantify the monetary value of job security. Design/methodology/approach The paper is theoretical and based on a financial economics human capital model. Empirical estimates of the annualized value of job security at three large corporations and at the government of the USA are also developed for an illustrative employee profile. Findings A financial economics human capital model can be used to derive a lower‐bound estimate for the monetary value of job security and empirical estimates can be calculated straightforwardly to help managers who allocate economic resources to fulfill organizational labor requirements or negotiate labor agreements. Research limitations/implications The model presented provides a lower‐bound estimate only. Future research could suggest approaches to calculate more precise estimates. Practical implications This paper provides a tool for managers and workers who wish to include the monetary value of relative job security in the definition of total compensation during the negotiation of employment conditions or while benchmarking total compensation. Originality/value This paper is a pioneer contribution in the field of quantifying the monetary value of job security.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 it