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Enregistrement W2327372734 · doi:10.1126/science.335.6074.1302-a

IEG's Role in Evaluating Climate Financing—Response

2012· article· en· W2327372734 sur OpenAlexaff
Simon D. Donner, Milind Kandlikar, Hisham Zerriffi

Notice bibliographique

RevueScience · 2012
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueEvaluation and Performance Assessment
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésCredibilityAuditInstitutionBusinessFinancial institutionAccountingIndependence (probability theory)Corporate governanceFinancePolitical science

Résumé

récupéré en direct d'OpenAlex

Heider asserts the importance of avoiding bias or conflict of interest in evaluating the impacts of climate change financing. We could not agree more. Independent and transparent auditing of the Green Climate Fund (GCF) and other climate change financing is not only critical to minimizing waste, but also to building the public and political will necessary to provide financial support to the developing world. We recognize that internal auditing bodies such as the Independent Evaluation Group (IEG) of the World Bank Group try to maintain independent governance structures and implement institutional mechanisms aimed at minimizing bias in project evaluation. Unfortunately, there is substantial evidence that historical and on going ties between an auditor and the aid institution create the potential for both actual and perceived bias in project evaluation. Maintaining independence and credibility is a challenge for independent evaluation offices because of shared culture and personnel. There is a revolving door between international development institutions and their internal evaluation groups ([ 1 ][1]–[ 3 ][2]). For example, a majority of the current upper management (directors, managers, program leaders, and advisers) at the IEG are former World Bank employees, in some cases for decades. The IEG itself is housed within the World Bank headquarters. It is unlikely that evaluators with long-term ties to the aid institution can conduct investigations free from concern about potential repercussions on a future career in the institution ([ 1 ][1]). Even if the evaluators are independent, the culture of the institution still affects their outlook and their methods. An external review of the Internal Evaluation Office of the International Monetary Fund (IMF) found that evaluators were often unable to think outside the box due to the influence of IMF culture and recommended that outsiders be recruited to bring fresh personalities, perspectives, and questioning attitudes ([ 1 ][1]). It is for these cultural reasons that there have been calls for evaluations of aid institutions to be conducted by people without ties to the institutions ([ 3 ][2]–[ 5 ][3]). In the case of climate change financing, the perception of the trustees and the auditing process could influence whether donor nations meet funding pledges and whether recipient nations trust financing programs. Regardless of recent initiatives to increase aid effectiveness and introduce a culture of learning to aid institutions, the perception of a conflict of interest between the auditor and the aid institution would remain. As Heider notes, this problem would not be solved by delegating evaluation to a single outside entity that could become financially dependent on the institutions it was meant to monitor. These actual and perceived conflicts of interest can be minimized by engaging a loose, third-party network of auditors through an academic-style peer review system. The internal evaluation divisions at the development banks and aid agencies would still be key players in such a system. For example, if the World Bank becomes the GCF trustee, the IEG could play a more editorial role that includes collecting project data, coordinating the external evaluation process, and reporting results of that process to the GCF Board. This approach would take advantage of the strengths of the IEG while providing the type of transparent auditing necessary to build the political and public confidence in the climate change financing system. 1. [↵][4] 1. K. Lissakers, 2. I. Husain, 3. N. Woods , Report of the External Evaluation of the Independent Evaluation Office (International Monetary Fund, Washington, DC, 2006). 2. 1. C. Weaver , Rev. Int. Org. 5, 365 (2010). [OpenUrl][5][CrossRef][6] 3. [↵][7] 1. A. Lerrick , “Is the World Bank's word good enough?,” Testimony before the U.S. Senate Foreign Relations Committee, Hearing on Multilateral Development Banks (U.S. Government Printing Office, Washington, DC, 2006). 4. 1. R. Levine , “Evaluating development aid effectiveness,” Testimony before the U.S. Senate Foreign Relations Committee, Hearing on Multilateral Development Banks (U.S. Government Printing Office, Washington, DC, 2006). 5. [↵][8] 1. W. Easterly , “Accountability for multilateral development banks,” Testimony before the U.S. Senate Foreign Relations Committee, Hearing on Multilateral Development Banks (U.S. Government Printing Office, Washington, DC, 2006). [1]: #ref-1 [2]: #ref-3 [3]: #ref-5 [4]: #xref-ref-1-1 View reference 1 in text [5]: {openurl}?query=rft.jtitle%253DRev.%2BInt.%2BOrg.%26rft.volume%253D5%26rft.spage%253D365%26rft_id%253Dinfo%253Adoi%252F10.1007%252Fs11558-010-9094-1%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [6]: /lookup/external-ref?access_num=10.1007/s11558-010-9094-1&link_type=DOI [7]: #xref-ref-3-1 View reference 3 in text [8]: #xref-ref-5-1 View reference 5 in text

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,051
score de la tête « metaresearch » (Gemma)0,119
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,051
Score d'incertitude au seuil0,268

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0510,119
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,003
Études des sciences et des technologies0,0050,012
Communication savante0,0160,010
Science ouverte0,0050,021
Intégrité de la recherche0,0220,022
Charge utile insuffisante (le modèle a refusé de juger)0,0110,006

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.

Tête enseignante Opus0,277
Tête enseignante GPT0,575
Écart entre enseignants0,299 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations31
Publié2012
Routes d'admission1
Résumé présentoui

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