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Enregistrement W6949469377 · doi:10.5281/zenodo.13682638

Report on transformative indicators initiatives for a sustainable wellbeing paradigm

2024· article· en· W6949469377 sur OpenAlexaboutno aff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueQuality of Life Measurement
Établissements canadiensnon disponible
Organismes subventionnairesEuropean Commission
Mots-clésTransformative learningDeliverableCraftCorporate governanceQuality (philosophy)Sustainable developmentConceptual frameworkEuropean unionSustainability

Résumé

récupéré en direct d'OpenAlex

Recognizing that each indicator set, or index emerges from specific initiatives with distinct goals, actors, and contexts, this research sets out to examine the initiatives themselves to uncover the broader implications and uses of the metrics they generate. In doing so, this deliverable explores the potential of Transformative Indicators Initiatives (T-IIs) to reshape policymaking within the European Union (EU), aiming to overcome the pre-eminence of conventional socio-economic evaluations such as GDP. As the national initiatives analysed in this study as well as the relevant literature on “beyond-GDP” indicators demonstrate, the biggest challenges related to enforcing sustainable wellbeing metrics at top levels of governance do not lie in the ex-ante definition of “the right” or “the best” indicators, but in being aware of a series of technical quality, theoretical adequacy, and potential of amplification challenges. This is why, rather than proposing a definit(iv)e list of indicators to be readily adopted, we craft a framework for the elaboration of a dashboard that keeps up with the theoretical as well as practical state of the art in transformative sustainable wellbeing indicators. The report is structured around three main phases: conceptualization, empirical analysis, and recommendations, with a focus on defining, analysing, and proposing pathways toward a T-II for the EU. By integrating theoretical insights with practical examples, this study aims to establish a foundation for a future where indicators not only measure but also inspire and enact change. Conceptual phase – Defining Transformative Indicators Initiatives The study begins by defining T-IIs through a combination of quality criteria, theoretical adequacy criteria, and impact reach criteria, grounded in sustainable transition studies. This phase characterizes T-IIs not just as measurement tools, but as sets of norms, rules, principles, actors, and institutions that support alternative measurement practices oriented toward transformations aligned with sustainable wellbeing paradigms. The conceptualization emphasizes that T-IIs should influence socio-economic realities beyond merely measuring them, aiming to reshape or replace prevailing paradigms to better align with sustainable wellbeing. Empirical phase – Illustrating Transformative Indicators Initiatives The analysis involved a comprehensive review of eight existing IIs0F0F[1], assessing their alignment with T-II criteria developed in the conceptual phase. This phase revealed three distinct groups of IIs—informist, reformist, and transformist—, each displaying varying degrees of proximity with our quality, theoretical, and impact criteria. The review highlighted strengths and areas for improvement in these initiatives, particularly in terms of their ability to integrate ecological considerations and their effectiveness in influencing policy and socio-economic norms. Recommendation phase – Designing an EU Transformative Indicators Initiative Drawing on insights from the two previous phases, and a roundtable dialogue with EU practitioners, the third phase worked out the concept of a feasible and desirable T-II for the EU. The discussion emphasizes the integration of the T-II into the EU’s Impact Assessment mechanisms, advocating for a co-constructed approach with institutional stakeholders and citizens, and enhanced resource optimization among existing agencies. Conclusions Our final proposition for an EU T-II consolidates the findings from the theoretical, empirical, and recommendation phases of this study into a framework designed to guide EU policymaking towards the design of a transformative sustainable wellbeing indicators initiative. The final proposition for an EU T-II integrates theoretical and empirical insights with the practical realities shared by EU practitioners. For quality criteria, we advocate for standards that ensure accuracy, reliability, robustness, timeliness, coherence, comparability, accessibility, and clarity. The theoretical framework should be holistic, boundary-limited, systemic, and integrate individual, societal, and planetary wellbeing domains. For the impact criteria, we suggest drawing on the roundtable’s recommendations but also pushing closer to an ideal T-II, inspired by the transformative approaches observed in the “transformist” group of IIs identified in our analysis. This involves integrating the T-II into the EU’s Impact Assessment mechanisms to enhance decision-making processes, establishing a mix of quantitative and qualitative indicator targets, and optimizing resources to foster synergies among existing frameworks and agencies. This comprehensive approach aims to position the EU at the forefront of global efforts to integrate sustainable wellbeing into policymaking. By adopting this transformative framework, the EU can catalyse significant socio-economic changes that align with long-term sustainability goals, setting a global standard for others to follow. [1] The eight IIs are the Measuring What Matters Dashboard of Australia, the Gross National Happiness Index of Bhutan, the Canadian Index of Wellbeing of Canada, the New Indicators of Wealth of France, the Equitable and Sustainable Wellbeing Indicators of Italy, the Living Standards Framework Dashboard from New Zealand, the National Performance Framework Dashboard of Scotland, and the National Wellbeing Indicators of Wales.

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)0,025
score de la tête « metaresearch » (Gemma)0,034
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: aucune
GenreSignal candidat: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,025
Score d'incertitude au seuil0,132

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0250,034
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0040,004
Études des sciences et des technologies0,0030,003
Communication savante0,0100,008
Science ouverte0,0020,013
Intégrité de la recherche0,0040,007
Charge utile insuffisante (le modèle a refusé de juger)0,0140,005

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 Opus0,059
Tête enseignante GPT0,331
Écart entre enseignants0,272 · 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
GenreSynthèse

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

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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