Measuring Total Employer Cost of Compensation for Teachers in Eight K-12 Public Schools in Oregon, Washington, and Idaho
Bibliographic record
Abstract
To test the feasibility of applying its ”Total Employer Cost of Compensation” (TECC) analytical framework to K-12 school personnel, the Center for Public Service (CPS) collected and validated data from five Oregon school districts (Beaverton, Hillsboro, Lake Oswego, Salem-Keizer, and Portland), along with two in Washington State (Seattle and Vancouver) and one in Idaho (Boise). The four main categories of TECC costs – salary; employer-paid health care; retirement benefits; and the value of paid time off (PTO) – were then calculated for several different K-12 teacher “archetypes” – e.g., Entry-level teachers with a BA degree; Mid-stage teachers with an MA degree and 10 years’ experience; and Latter-stage teachers with 30 years’ experience and an MA degree with additional graduate credits.
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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) | 0.001 | 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".