What is Social Innovation and How is it Done?
Notice bibliographique
Résumé
Every truth passes through three stages. First, it is ridiculed. Second, it is violently opposed. Finally, it is taken to be self-evident. Introduction The first two decades of the 21st century brought burgeoning interest in social innovation – its nature, needs, possibilities and dilemmas. There were new policies; funds; research studies; accelerators; emerging fields around design, the maker movement, open data and the sharing economy, climate transition and social justice; and action involving many hundreds of thousands of people, from Canada to China, Sweden to South Africa, with benefits reaching billions. This effervescence marked a shift in perception of both ends and means. It grew out of a recognition that too much innovation was being directed to the wrong ends – to warfare and killing; to the needs of the rich; or to trivial or harmful purposes. Too many of the world's most creative brains were working on the wrong tasks, while the world's most urgent needs were left underserved. Just as important was a shift in thinking about means: a recognition that innovation had become too focused on hardware and things, and that it was far too much an elite preoccupation, for the well-educated and well-connected in big cities, with far too little role for the rest in making and shaping. So, attention turned to how to make innovation more inclusive; how to tap into household innovators; civil society; and the creativity of communities. In both respects social innovation fed off a widespread desire of people to take more control of their lives and their futures and a dissatisfaction with existing institutions. As I show later in this book, this is a story in progress, and still in its early stages. But it has allowed us to see the past, the present and the future in a quite different light. The heritage of social innovation Much of what we take for granted in social life began as radical innovation, the work of dreamers not content just to dream. A century ago few believed that ordinary people could be trusted to drive cars at high speed; the idea of a national health service freely available to all was seen as absurdly utopian; the concept of a ‘kindergarten’ was still considered revolutionary; and in 1900 only one country had given women the vote.
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 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 | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».