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Record W6920160568 · doi:10.6068/dp14bad422fa659

Trend 1991 - 2050. United States Census Bureau. Components of Population Change - International: Fertility Rate for Age 20 - 24 | Country: Canada, 1991-2050. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 001-036-016.

2015· other· en· W6920160568 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCensusPopulationPopulation statisticsFertilityTotal fertility rateDemographic analysisProjections of population growthPopulation growthDemographic statistics

Abstract

fetched live from OpenAlex

United States Census Bureau (2015). Components of Population Change - International: Fertility Rate for Age 20 - 24 | Country: Canada, 1991-2050. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 001-036-016. Dataset: Presents estimates and projections of the fertility rate among women ages 20-24, by nation. The rate is reported as births per 1,000 women in the age group. This dataset, part of the United States Census Bureau’s International Database, shows population size and projections, components of change, and rates of growth and natural increase, for over 200 countries and world regions with a population of over 5,000 and that are recognized by the US State Department. The demographic components of population change presented include births, deaths, and net migration. Data are reported from 1950 and projected to 2050. Census Bureau demographers analyze data from censuses, surveys, vital statistics, and administrative records provided by national statistics offices, as well as data on international migration and refugee movements. The process involves data collection, evaluation, and analysis to develop a set of consistent estimates and projections of population, fertility, mortality, and international migration. The projections are generated using the Census Bureau's Rural/Urban Projection(RUP) software program, which projects population, by single years of age, for each calendar year beyond a base year. This approach means the Census Bureau fertility and mortality estimates pertain to specific years and thus year-specific estimates of fertility, mortality, and migration reflect the impact of natural disasters, civil conflicts, and changes in the health climate in a countryThe use of the RUP progam applies to all nations except the United States. US population projections and estimates are developed using US decennial census counts and vital statistics and other data on international migration. Category: Health and Vital Statistics, Population and Income Source: United States Census Bureau The United States Census Bureau is a bureau of the United States 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 United States foreign trade statistics. The first United States census was conducted in 1790 for the purposes of apportioning state representation in the House of Representatives of the United States and for the apportionment of taxes. http://www.census.gov Subject: Population Change, Young Adults, Fertility Rates, Females

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)0.013
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 score0.060
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.022
Science and technology studies0.0020.000
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0600.043

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 head0.114
GPT teacher head0.325
Teacher spread0.210 · 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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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