RANKING: United States Census Bureau. American Community Survey Summary File: 5-Year Estimates, 2011-2015: B25064. Median Gross Rent | State: Ohio | Demographic Indicator: Median Gross Rent, 2015. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 001-050-418
Bibliographic record
Abstract
United States Census Bureau. American Community Survey Summary File: 5-Year Estimates, 2011-2015: B25064. Median Gross Rent | State: Ohio | Demographic Indicator: Median Gross Rent, 2015. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 001-050-418 Dataset: Presents an estimate of median gross rent of renter-occupied housing units that pay cash rent in the United States, and state, county, metropolitan statistical area, census tract, and congressional district. Gross rent is the contract rent (rent agreed to or contracted) plus the estimated average monthly cost of utilities (electricity, gas, and water and sewer) and fuels (oil, coal, kerosene, wood, etc.) if these are paid by the renter (or paid for the renter by someone else). Median gross rent divides the gross rent distribution into two equal parts, with one-half of the cases falling below the median gross rent and one-half above the median, rounded to the nearest whole dollar. The dollar values presented are inflated to the latest year’s dollar values by multiplying by a factor equal to the average annual Consumer Price Index (CPI-U-RS) factor for the current year, divided by the average annual CPI-U-RS factor for the earlier/earliest year. The American Community Survey (ACS) conducted by the US Census Bureau provides estimates of the characteristics of the population over a specific time period. The ACS collects data from the 50 states, Washington, DC, and Puerto Rico, where it is called the Puerto Rico Community Survey. It is a continuous survey, in which each month a sample of housing unit addresses receives a questionnaire, with approximately three million addresses surveyed each year. Each year the survey produces data pooled to produce 1-year, 3-year, and 5-year estimates for geographic areas in the US and Puerto Rico, ranging from neighborhoods to congressional districts to the entire nation. Data for each release of the 5-year estimates were collected over a 5-year period ending December 31 of the reference year (eg, data in the 2012 5-year estimates were collected January 1, 2008 - December 31, 2012). The statistics reported represent the characteristics of the population for the entire period vs a specific year within that period. The 5-year estimates are published for areas with populations of all sizes and are the most reliable and precise of the ACS period estimates as well as the most comprehensive, albeit the least current. (The 1-year and 3-year estimates provide data on areas with populations of 65,000+ and 20,000+, respectively). The ACS estimates provide information about the social and economic needs of communities and are used to help determine how more than $400 billion in federal and state funds are distributed each year. It is conducted under the authority of Title 13, United States Code, Sections 141 and 193. Note that counts of the population are provided by the Census of Population and Housing conducted by the US Census Bureau every 10 years; and official estimates of the population are derived from the previous census and from the Census Bureau’s Population Estimates Program. https://www.census.gov/programs-surveys/acs/data.html Category: Housing and Construction, Prices, Consumption, and Cost of Living Subject: Utilities, Housing Market, Rents, Rental Housing, Housing Costs Source: United States Census Bureau The US Census Bureau is a bureau of the US Department of Commerce. The major functions of the Census Bureau are authorized by Article 2, Section 2 of the United States Constitution, which provides that a census of population shall be taken every 10 years, and by Title 13 and Title 26 of the United States Code of Federal Regulations. The Census Bureau is responsible for numerous statistical programs, including census and surveys of households, governments, manufacturing and industries, and for US foreign trade statistics. The first US census was conducted in 1790 for the purposes of apportioning state representation in the US House of Representatives and for the apportionment of taxes. http://www.census.gov
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.019 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.204 | 0.224 |
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".