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Record W6976980473 · doi:10.6068/dp15e85e3599823

Trend 2013 - 2016. Bureau of Labor Statistics. Consumer Expenditures: Age of Reference Person: Under 25 | Country: USA | Category: Housing | Socioeconomic Indicator*: Cellular phone service, 2013-2016. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 002-008-023.

2017· other· en· W6976980473 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRespondentSocioeconomic statusCensusPhoneMicrodata (statistics)Sample (material)Consumer Expenditure SurveyHousekeepingWages and salariesQuarter (Canadian coin)

Abstract

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Bureau of Labor Statistics (2017). Consumer Expenditures: Age of Reference Person: Under 25 | Country: USA | Category: Housing | Socioeconomic Indicator*: Cellular phone service, 2013-2016. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 002-008-023. Dataset: Age of reference person. Reference person is the first member mentioned by the respondent when asked to "Start with the name of the person or one of the persons who owns or rents the home." It is with respect to this person that the relationship of the other consumer unit members is determined. The Consumer Expenditure Survey is a nationwide survey conducted annually for the Bureau of Labor Statistics (BLS) by the United States Census Bureau. The consumer expenditures program consists of two surveys--the Quarterly Interview Survey and the Diary Survey--that provide information on the characteristics, expenditures, and income of American consumers. For the diary survey, respondents complete a diary of expenses for two consecutive 1-week periods. The diary survey is designed to obtain data on frequently purchased items, such as food or housekeeping supplies, that respondents are less likely to recall over time. For the interview survey, respondents report data to an interviewer. Each sample household is interviewed once per quarter, for five consecutive quarters. This survey is designed to collect data on major items of expense, such as property purchases or vehicle purchases, and those that occur on a regular basis, such as rent or utility payments, that respondents recall for 3 months or longer. Each year approximately 30,000 persons participate in the Quarterly Interview Survey, and 15,000 participate in the Diary Survey. The dataset presents annual income and expenditures integrated from the Interview and Diary surveys in varying detail, classified by income, age, consumer unit size, and other demographic characteristics of consumer units. Expenditures consist of the transaction costs, including excise and sales taxes, of goods and services acquired during the interview or recordkeeping period. In many cases the hierarchy used to display the expenditure items will indicate the scope of a particular category. For example, the hierarchy shows that Entertainment covers events requiring admissions, pets and toys, entertainment equipment, and outdoor recreational equipment. Additional detail can be found in the BLS Glossary: http://www.bls.gov/cex/csxgloss.htm Expenditures consist of the transaction costs, including excise and sales taxes, of goods and services acquired during the interview or recordkeeping period. Detailed inclusions and exclusions for expenditure categories are available on the BLS web site. Category: Population and Income, Prices, Consumption, and Cost of Living 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/ Subject: Consumer Behavior, Home Ownership, Consumers, Age, Consumer Spending

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.132
Threshold uncertainty score0.412

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.021
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.018
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1230.137

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.

Opus teacher head0.058
GPT teacher head0.304
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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