Evaluating a Wellness Program for UNI Faculty and Staff: Preparing for a Cost-Benefit Analysis
Bibliographic record
Abstract
The University of Northern Iowa (UNI) paid total annual employer medical premiums of $17,967,000 for 2008, an increase of 7.37% from 2007. If medical premiums continue to increase at this rate, UNI will pay $29,556,720 in annual medical premiums in 2015. UNI is not alone in facing rising healthcare costs. Healthcare costs were identified as the "most serious challenge to their bottom line" by 41. 7 percent of the employers in a survey by the National Association of Professional Employer Organizations (Kumar 2009). The Business Roundtable Fourth Quarter 2007 CEO Economic Outlook Survey confirms these results with CEO's ranking the cost of health care as "the single biggest threat to company profits" (Adams 2008). To combat these costs, businesses have cut benefits, shifted costs to employees, and fired unhealthy workers (Armour 2005). Employee wellness programs are surpassing these responses in popularity, however, and are gaining the reputation as an effective response to the threat of healthcare costs (Goetzel 2008).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".