TREND: United States Census Bureau, Bureau of Labor Statistics. Current Population Survey: Labor Force Statistics: Unemployed | Seasonally Adjusted: Seasonally Adjusted | Demographic Indicator: Unemployment Level - 16-19 yrs., Black or African American Women, 1972/1 - 2015/2. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 002-026-010
Bibliographic record
Abstract
United States Census Bureau, Bureau of Labor Statistics. Current Population Survey: Labor Force Statistics: Unemployed | Seasonally Adjusted: Seasonally Adjusted | Demographic Indicator: Unemployment Level - 16-19 yrs., Black or African American Women, 1972/1 - 2015/2. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 002-026-010 Dataset: Reports estimates of the civilian noninstitutional population ages 16 and older that are unemployed and looking for full-time work. Estimates are segmented by sociodemographic characteristics. Unemployed persons are all those who: 1) had no employment during the reference week; 2) were available for work, except for temporary illness; and 3) had made specific efforts, such as contacting employers, to find employment sometime during the 4-week period ending with the reference week. Persons who were waiting to be recalled to a job from which they had been laid off need not have been looking for work to be classified as unemployed. Full-time work is defined as working 35 hours or more (at all jobs combined). The Current Population Survey is a monthly survey of the civilian noninstitutional population ages 16 and older conducted with a probability sample of 60,000 households in the United States by the Census Bureau for the Bureau of Labor Statistics. The resulting Labor Force Statistics dataset, presented here, provides a comprehensive body of information on the employment and unemployment experience of the nation's population, classified by age, sex, race, and other characteristics. Data are collected by personal and telephone interviews. The survey reference period is the calendar week (Sunday through Saturday) that includes the 12th day of the month; the actual survey is conducted during the following week, ie, the week containing the 19th day of the month. Basic labor force data are gathered monthly; data on special topics are gathered in periodic supplements. Persons less than 16 years of age are excluded from the official estimates because child labor laws, compulsory school attendance, and general social custom in the US severely limit the types and amount of work that children under age 16 can do. (Prior to 1948, the sampled population included those ages 14 and older.) Persons on active duty in the US Armed Forces are excluded from coverage, as is the institutional population, which consists of residents of penal and mental institutions and homes for the aged and infirm. Seasonally adjusted and nonadjusted estimates are included in the dataset. Seasonal adjustments make it easier to observe the cyclical and other nonseasonal movements in the series. In evaluating changes in a seasonally adjusted series, it is important to note that seasonal adjustment is merely an approximation based on past experience. Seasonally adjusted estimates have a broader margin of possible error than do the original data on which they are based, because they not only are subject to sampling and other errors but also are affected by the uncertainties of the seasonal adjustment process itself. Since January 1980, national labor force data have been seasonally adjusted with a procedure called X-11 ARIMA (Auto-Regressive Integrated Moving Average). Statistics are presented for the nation in total, by the month, quarter, and year, where available. http://download.bls.gov/pub/time.series/ln/ Category: Population and Income, Labor and Employment Subject: Labor Force Status, Unemployed Workers, Unemployment, Civilian Labor Force, Sociodemographic Characteristics, Employment Status Source: Bureau of Labor Statistics The Bureau of Labor Statistics (BLS) of the United States Department of Labor is the principal fact-finding agency for the federal government in the broad field of labor economics and statistics. The BLS is an independent national statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the US Congress, other federal agencies, state and local governments, business, and labor. The BLS also serves as a statistical resource to the Department of Labor. http://www.bls.gov/
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.018 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.080 | 0.090 |
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".