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Record W6939049385 · doi:10.6068/dp16988567f7d26

RANKING: United States Census Bureau. US International Trade in Goods and Services: Trade Balance - Total, 2017. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 001-022-001

2019· other· en· W6939049385 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCensusBalance of paymentsBalance of tradeProduct (mathematics)Goods and servicesCommodityGovernment (linguistics)Official statisticsBalance (ability)

Abstract

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datasets.shared.infosheet.CitationMgr@34a Dataset: Balance on goods and services: this is the record of the difference between exports of goods and services and imports of goods and services. In the broad sense, this balance is conceptually equal to net exports of goods and services, which is a component of gross domestic product (GDP). This dataset, also known as the FT900 data release, provides the official import and export statistics of the United States. The data summarizes government and nongovernment shipments of merchandise between foreign countries and the US Customs Territory (the 50 states, Washington, DC, and Puerto Rico), US Foreign Trade Zones, and the US Virgin Islands. Excluded are shipments between the US and its territories and possessions; transactions with US military, diplomatic, and consular installations abroad; US goods returned to the US by its Armed Forces; personal and household effects of travelers; and in-transit shipments. Data are shown on a balance of payments (BOP) basis. The import statistics consist of goods valued at more than $2,000 per commodity shipped by individuals and organizations (including importers and customs brokers) into the US from other countries. Import duties, freight, insurance, and other charges incurred in bringing merchandise to the United States are excluded. Statistics for over 95 percent of all imported goods shipments are compiled from records filed electronically with Customs and Border Protection and forwarded as computer tape files to the US Census Bureau. Statistics for other transactions are compiled from hard-copy documents filed with Customs and Border Protection. Export statistics consist of goods valued at more than $2,500 per commodity shipped by individuals and organizations from the US to other countries. Statistics for exported goods transactions are compiled from documents filed with Customs and Border Protection, and comparable data in electronic form submitted directly by exporters and their agents and from Canada. For imports, the value reported is the US Customs and Border Protection appraised value of merchandise; generally, the price paid for merchandise for export to the United States. Exports are valued at the f.a.s. (free alongside ship) value of merchandise at the US port of export, based on the transaction price including inland freight, insurance, and other charges incurred in placing the merchandise alongside the carrier at the US port of exportation. https://www.census.gov/foreign-trade/statistics/historical/index.html Category: International Relations and Trade Subject: International Trade, Trade Balance, Imports, Balance Of Payments, Exports, Merchandise 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. https://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 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)0.001
metaresearch head score (Gemma)0.010
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 score0.110
Threshold uncertainty score0.368

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.013
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.1100.117

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 head0.040
GPT teacher head0.296
Teacher spread0.257 · 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
Published2019
Admission routes1
Has abstractyes

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