A mega-index for the Americas and its underlying sustainable development correlations
Notice bibliographique
Résumé
Indicators and their composite indices have been embraced as development tools for guiding humanity toward a sustainable destination. In response, public and private organizations have generated hundreds of these metrics, making their application overwhelming to policymakers, planners, and scientists. Past reviews have revealed that a majority of common development indices have theoretical or quantitative shortcomings, supporting that there is no consensus regarding their theoretical basis, design, use, thresholds-of-effect, or validation. In response, this study was designed around four guiding research questions: (i) What are the underlying development themes within a collection of established sustainability indices, and what distinguishes winning locations from losing ones? (ii) Are the three major divisions of sustainability (economic growth, social equity, environmental integrity) equally represented by current sustainable development measuring initiatives? (iii) Could just a few common and freely available indicators capture all present dimensions of sustainable development? (iv) Would a new sustainable development mega-index research paradigm improve humanity’s ability to assess progress toward sustainability? Those questions were investigated using data from 30 mostly contiguous Western Hemisphere nations and three amassing methodological objectives. First, 31 known indices were reduced into underlying dimensions (factors) of sustainable development. Next, those factors were combined (aggregated) into the first mega-index of sustainable development (MISD). Finally, 11 common development indicators were explored regarding collinearity and explanatory power of the sustainable development dimensions and MISD. Seven latent dimensions (sub-metrics) captured over 85% of the variation of the original 31 indices, with socioeconomic themes dwarfing environmental ones. The factors conveyed: (F1) socioeconomic well-being synergies; (F2) economic freedom and democracy; (F3) environmentally efficient happiness; (F4) ecosystem wellbeing; (F5) peace to economic vulnerability tradeoff; (F6) natural resources protection; and (F7) environmental stewardship and risk resilience. MISD is the geometric mean of the seven sub-metrics,which were directed toward sustainability, and rescaled (normalized) 0 (worst case) to 100 (best case). Geographically, this study ranked Belize best overall, followed by Guyana, Panama, Uruguay, and Canada; Barbados ranked worst, preceded by Haiti, Trinidad and Tobago, Mexico, and Cuba. Winning countries were characterized by low population density, increased forestland, decreased urban, and larger country area. Child mortality and population growth rate remained negative predictors of socioeconomic conditions; however per-capita CO2 sacrificed ecological integrity for improved human well-being. Mega-index creation will serve as an important scientific stepping-stone for improving accuracy and simplifying valuations of sustainable development, thus others should follow.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 tête enseignante, 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 ».