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Past and projected GDP per capita growth in Southeast Asia

2017· other· en· W4400637520 on OpenAlexfundno aff

Bibliographic record

VenueOECD agricultural outlook .../OECD-FAO agricultural outlook · 2017
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaChinese Academy of Agricultural SciencesEconomic Research ServiceEuropean CommissionU.S. Environmental Protection Agency
KeywordsPer capitaSoutheast asiaGross domestic productReal gross domestic productEconomicsGeographyEnvironmental scienceAgricultural economicsEconometricsDemographyEconomic growthAncient historyHistorySociology

Abstract

fetched live from OpenAlex

The food and agriculture sector is faced with a critical global challenge: to ensure access to safe, healthy, and nutritious food for a growing world population, while at the same time using natural resources more sustainably and making an effective contribution to climate change adaptation and mitigation.Through this annual collaboration and other studies, the Organisation for Economic Co-operation and Development (OECD) and the Food and Agriculture Organization of the United Nations (FAO) are working together to provide information, analysis and advice, to help governments achieve these essential objectives.This is the 13th joint edition of the OECD-FAO Agricultural Outlook.It provides ten-year projections to 2026 for the major agricultural commodities, as well as for biofuels and fish.The pooling of market and policy information from experts in a wide range of participating countries provides a benchmark necessary for assessing the opportunities and threats to the sector.This year's Agricultural Outlook includes a special focus on Southeast Asia, a region where agriculture and fisheries have developed rapidly and undernourishment has been significantly decreased, but also a region that is on the front line of the effects of climate change and where there are rising pressures on natural resources.The Agricultural Outlook comes in the context of a wider set of international efforts to address food security and agricultural issues.Two global initiatives stand out:• The UN Sustainable Development Goals (SDGs) set ambitious targets to be achieved by 2030.Among these, the first goal is to end poverty in all its forms everywhere, while the second goalTThe Agricultural Outlook, 2017-2026, is a collaborative effort of the Organisation for Economic Co-operation and Development (OECD) and the Food and Agriculture Organization (FAO) of the United Nations.It brings together the commodity, policy and country expertise of both organisations and input from collaborating member countries to provide an annual assessment of prospects for the coming decade of national, regional and global agricultural commodity markets.The baseline projection is not a forecast about the future, but rather a plausible scenario based on specific assumptions regarding macroeconomic conditions, agriculture and trade policy settings, weather conditions, longer term productivity trends and international market developments.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.370
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.014

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 head0.013
GPT teacher head0.201
Teacher spread0.188 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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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