Map of Counties (2010). United States Census Bureau. 2010 US Census of Population and Housing: Summary File 1: Group Quarters Population in Nursing Facilities/Skilled-Nursing Facilities by Sex by Age | Country: USA | State: New Hampshire | Description*: Total Population, 2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 001-045-245.
Bibliographic record
Abstract
Conquest Statistical Datasets. (2014). 2010 US Census of Population and Housing: Summary File 1: Group Quarters Population in Nursing Facilities/Skilled-Nursing Facilities by Sex by Age, 2010 - 2010 [Data file]. Retrieved from http://www.data-planet.com Dataset: Presents a count of the group quarters population in the United States living in nursing and skilled-nursing facilities by sex by age. Counts are reported by state, segmented by county. Group quarters are places where people live or stay in a group living arrangement, which are owned or managed by an entity or organization providing housing and/or services for the residents. These services may include custodial or medical care as well as other types of assistance, and residency is commonly restricted to those receiving these services. People living in group quarters are usually not related to each other. Group quarters include such places as college residence halls, residential treatment centers, skilled-nursing facilities, group homes, military barracks, correctional facilities, and workers dormitories. Two types of group quarters are distinguished: Institutional, ie, facilities that house those who are primarily ineligible, unable, or unlikely to participate in the labor force while residents; and Noninstitutional, ie, facilities that house those who are primarily eligible, able, or likely to participate in the labor force while residents. The United States Census Bureau’s Summary File 1 (SF1) presents data from the 2010 decennial Census of Population and Housing. The US Census counts every resident in the United States every 10 years, as mandated by Article I, Section 2 of the Constitution. The data collected by the decennial census are used to determine the number of seats each state has in the US House of Representatives and to allocate federal funds to local communities. The SF1 contains 100 percent of data asked of all people and about every housing unit. The dataset includes population and housing characteristics for the total population, population totals for an extensive list of race (American Indian and Alaska Native tribes, Asian, and Native Hawaiian and Other Pacific Islander) and Hispanic or Latino groups, and population and housing characteristics for a limited list of race and Hispanic or Latino groups. Presented here are 177 population tables (identified with a "P") and 58 housing tables (identified with an "H") shown down to the block level; 82 population tables (identified with a "PCT") and 4 housing tables (identified with an "HCT") shown down to the census tract level; and 10 population tables (identified with a "PCO") shown down to the county level, for a total of 331 tables. There are 14 population tables and 4 housing tables shown down to the block level and 5 population tables shown down to the census tract level that are repeated by the major race and Hispanic or Latino groups. Category: Health and Vital Statistics, Population and Income Source: United States Census Bureau Subject: Rehabilitation Facilities, Age, Gender, Population, Nursing Homes
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.017 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.146 | 0.104 |
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 source (direct Gemma or distilled Codex), 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".