TREND: World Trade Organization. WTO Annual Trade in Merchandise and Services: Merchandise - Imports | Country: Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burma, Burundi, Cambodia, Cameroon, Canada, Cape Verde, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo (Brazzaville), Congo (Kinshasa), Cook Islands, Costa Rica, Cote D'Ivoire, Croatia, Cuba, Cyprus, Czech Republic, Denmark, Djibouti, Dominica, Dominican Republic, East Germany, East Timor, Ecuador, Egypt | Indicator: Textiles, 1980 - 2017. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 082-001-003
Notice bibliographique
Résumé
World Trade Organization. WTO Annual Trade in Merchandise and Services: Merchandise - Imports | Country: Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burma, Burundi, Cambodia, Cameroon, Canada, Cape Verde, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo (Brazzaville), Congo (Kinshasa), Cook Islands, Costa Rica, Cote D'Ivoire, Croatia, Cuba, Cyprus, Czech Republic, Denmark, Djibouti, Dominica, Dominican Republic, East Germany, East Timor, Ecuador, Egypt | Indicator: Textiles, 1980 - 2017. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 082-001-003 Dataset: Reports merchandise imports by region, selected regional agreements, and economy. Statistics on merchandise trade cover total merchandise retained exports by region, selected regional agreements, and economy. Breakdowns by major commodity groups for individual economies, selected regional trade agreements, and regions at the total level are also included. Commodity groups are based on the SITC product nomenclature. Reports exports and imports of commercial services and merchandise trade. Statistics on trade in commercial services are sourced from the IMF Balance of Payments Statistics and from the Trade in Services by Partner Country dataset of the OECD. Data for European Union members, EU candidate and EU observer countries as well as the EU(28) aggregate are drawn from Eurostat. For some economies, data are drawn from national sources. Where possible, reported data are complemented by estimations produced by the WTO, UNCTAD and ITC. Merchandise trade statistics are mainly sourced from national sources and complemented with estimations produced by the WTO. Data for individual European Union members are drawn from Eurostat. Additional data sources include UNSD COMTRADE, the IMF International Financial Statistics, and UNCTAD. For more information on the statistical sources, compilation methodologies and definitions of groups please refer to the Technical Documentation). https://www-wto-org.proxy.library.nyu.edu/english/res_e/statis_e/trade_datasets_e.htm Category: International Relations and Trade Subject: International Trade, Imports, Merchandise Source: World Trade Organization Established in 1995, the World Trade Organization (WTO) provides a forum for negotiating agreements aimed at reducing obstacles to international trade and ensuring a level playing field for all. The WTO also provides a legal and institutional framework for the implementation and monitoring of these agreements, as well as for settling disputes arising from their interpretation and application. The current body of trade agreements comprising the WTO consists of 16 different multilateral agreements (to which all WTO members are parties) and two different plurilateral agreements (to which only some WTO members are parties). As of 2018, the WTO has 164 members, of which 117 are developing countries or separate customs territories. WTO activities are supported by a Secretariat of some 700 staff, led by the WTO Director-General, located in Geneva, Switzerland. https://www-wto-org.proxy.library.nyu.edu/
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,004 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,070 | 0,092 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».