Overview of the Postcensal Estimates of Population by Age and Sex
Bibliographic record
Abstract
The population estimates by age and sex for Washington State counties are developed using the component method, which derives the estimated population by adding natural population change (births minus deaths) and net migration to the base year population. Two steps are taken prior to the estimation process. First, the group quarters population is subtracted from the base population (it is added back in at the end of the estimate process). Second, the base year population is aged one year forward. The following is the detailed description of the method: 1. For 2011 estimates, the 2010 Census population by single year of age and sex for each county is used as the base, and the estimates themselves will be used as base thereafter. 2. Group quarter population typically retains their age sex characteristics across a decade. So military, college/university, and prison populations are subtracted off the county population prior to the estimate process. 3. The population is aged one year forward. a. For the 2011 estimates, the population is aged in single year increments b. For estimates 2012 and later, the population data is categorized in five year intervals. One fifth of each five year interval is aged forward.
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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 | 0.000 |
| 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) | 0.000 | 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".