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Record W6976677021 · doi:10.6068/dp15e551f2e6c44

TREND: International Monetary Fund. International Financial Statistics: National Accounts | Country: Canada | ID: NGDP_R_PT | Indicator: Gross Domestic Product, Real, 1950/1 - 2016/4. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 056-015-010

2017· other· en· W6976677021 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsGross fixed capital formationNational Income and Product AccountsNational accountsGross domestic productMeasures of national income and outputConsumption (sociology)Balance of paymentsCommodityGoods and servicesGovernment (linguistics)

Abstract

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International Monetary Fund. International Financial Statistics: National Accounts | Country: Canada | ID: NGDP_R_PT | Indicator: Gross Domestic Product, Real, 1950/1 - 2016/4. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 056-015-010 Dataset: Summary data are presented for national accounts. Statistics include Household Consumption Expenditures, including Nonprofit Institutions Serving Households (NPISHs), Government Consumption Expenditure, Gross Capital Formation, Exports of Goods and Services, Imports of Goods and Services, Gross Domestic Product (GDP), as well as metrics associate with GDP volume. The summary data for national accounts are compiled according to the System of National Accounts (SNA). The database covers approximately 32,000 time series covering more than 194 countries and areas starting in 1948. Topics covered include balance of payments, commodity prices, exchange rates, fund position, government finance, industrial production, interest rates, international investment position, international liquidity, international transactions, labor statistics, money and banking, national accounts, population, prices, and real effective exchange rates. Data availability varies by country and time period. http://data.imf.org/?sk=5dabaff2-c5ad-4d27-a175-1253419c02d1&sid=1390030109571&ss=1452193181026 Category: Industry, Business, and Commerce, International Relations and Trade Subject: Consumption, Economic Conditions, Government Spending, Gross Domestic Product (GDP), Capital, Consumer Spending Source: International Monetary Fund Headquartered in Washington, DC, the International Monetary Fund (IMF) was conceived at a United Nations conference convened in Bretton Woods, New Hampshire, United States, in July 1944. The 44 governments represented at that conference sought to build a framework for economic cooperation that would avoid a repetition of the vicious circle of competitive devaluations that had contributed to the Great Depression of the 1930s. As of 2015, the IMF has 188 member countries. Its primary purpose is to ensure the stability of the international monetary system, specifically the system of exchange rates and international payments that enables countries (and their citizens) to transact with one other. This system is essential for promoting sustainable economic growth, increasing living standards, and reducing poverty. The Fund’s mandate has recently been clarified and updated to cover the full range of macroeconomic and financial sector issues that bear on global stability. The IMF is a specialized independent agency of the United Nations but has its own charter, governing structure, and finances. Its members are represented through a quota system broadly based on their relative size in the global economy. http://www.imf.org/

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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)0.016
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 score0.588
Threshold uncertainty score0.820

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0100.031
Science and technology studies0.0020.001
Scholarly communication0.0060.005
Open science0.0040.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1690.249

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 head0.023
GPT teacher head0.299
Teacher spread0.276 · 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
Published2017
Admission routes1
Has abstractyes

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