Notice bibliographique
Résumé
COP26 concluded with mixed results. It was the first formal opportunity since the 2015 Paris Agreement for countries to revise their nationally determined contributions (NDCs) for the 2030 targets and to offer long-term greenhouse-gas reduction strategies to 2050. Pledges were made. Early indications suggest that if the pledges covering about 90% of global emissions are followed by action and completed in full and on time, a temperature increase of around 1.8°C to 2.1°C by 2100 could be seen. But without stronger actions taken to 2030, the temperature will likely be higher, according to IPIECA. The Paris Agreement set a global framework “to avoid dangerous climate change by limiting global warming to well below 2°C and pursuing efforts to limit it to 1.5°C. It also aims to strengthen countries’ ability to deal with the impacts of climate change and support them in their efforts.” Even before COP26 began, a pledge made in 2009 and reaffirmed at the 2015 Paris meeting was stirring up frustration. A target was missed for rich countries to provide poor nations with $100 billion in aid each year to confront global warming. Current data show the goal, which was to have been met in 2020, won’t be reached until 2023—3 years later than agreed. The report was compiled by Canada’s Minister of Environment and Climate Change, Jonathan Wilkinson, and Germany’s Deputy Environment Minister, Jochen Flasbarth. They drew on international climate finance tracking data provided by the Organization for Economic Cooperation and Development. Flasbarth, quoted by the Associated Press, said, “Not all of our conversations were really (...) polite,” referring to talks that had taken place with rich and poor nations in recent weeks. A catch-up plan was drafted for COP26. Alok Sharma, the UK official who chaired the talks about this issue, said, “The plan provides confidence that the $100 billion will be met in 2023, and importantly, it projects that the $100 billion will be exceeded in subsequent years, with up to $117 billion being mobilized in 2025.” While it’s clear that much work needs to be done to move toward the temperature goal, it also can’t be denied that incremental progress has been made. Business models, practices, and operations have changed across the oil and gas industry and will continue to do so as energy transition, climate, and oil and gas prices drive decisions. A case in point was Shell’s announcement on 15 November that it intends to move its tax residence from the Netherlands to the UK, where it is incorporated. CEO Ben van Beurden and other top executives will move to a UK corporate headquarters. One of the reasons given was that “ … it’s even more important that we have an increased ability to accelerate the transition to a lower-carbon global energy system. A simpler structure will enable Shell to speed up the delivery of its Powering Progress strategy, while creating value for our shareholders, customers, and wider society.” COP27 is scheduled for December 2022 in Sharm El-Sheikh, Egypt. Another tallying of actions delivering on pledges will take place and the world will be watching—skeptics, supporters, and those who have acted to build the momentum toward the goal.
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 | 0,038 | 0,161 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,015 | 0,003 |
| Communication savante | 0,012 | 0,008 |
| Science ouverte | 0,006 | 0,009 |
| Intégrité de la recherche | 0,050 | 0,036 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,055 | 0,032 |
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 ».