The Political and Moral Economies of Science: A Case Study of Genomics in Canada and the United Kingdom
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Notice bibliographique
Résumé
The term political economy describes how nations organize the production and use of wealth. Following from this definition, the political economy of science can be understood as the role that scientific activity plays, or is thought to play, in national economies and the related policies and agendas that structure this contribution. A moral economy, according to Robert E. Kohler (1), is based on the social rules and customs that regulate a community. Norms about merit, reciprocity, reward, professionalism and acceptable scientific practice all contribute to the moral economy of science. Although the political and moral economies of science operate on vastly different scales, I argue, using the case of genomics in Canada and the United Kingdom, that they are co-produced. The concept of co-production (2) is used here to emphasize that both the high-level science policy context and the local culture of genomics influence each other and that neither can be understood as the primary driver for change. Rather, evidence shows that change is occurring simultaneously at both levels and that, in the case of genomics, there is a resonance between shifting science policy and shifting scientific culture. In both Canada and the United Kingdom, science is increasingly aligned with economic growth and national innovation. Scientific activity has long been assumed to provide economic and social benefits. However, starting in the 1980s, government policies and funding regimes, particularly those coming out of the Thatcher government in the United Kingdom, began to emphasis the economic dimension of scientific research. Over the last two decades, science policy agendas in both countries have shifted from supporting research based on assumed, indirect economic and social benefit toward a model that expects direct and demonstrated economic results from research. Changes in the moral economy of science have been demonstrated through studies showing that norms, attitudes, and practices are becoming more entrepreneurial in spirit. In particular, the notion of personal financial gain is becoming compatible with traditional norms around scientific merit and reward. The adoption of entrepreneurial attitudes and activities is by no means universal; however, patenting activity and researcher surveys in the life sciences suggest that a shift in favour of commercially oriented activities is underway. (3) There are a number of bridges that link the political and moral economies of science, allowing them to exert influence on one another. Universities and academic institutions are one of the more obvious points of connection. Institutional norms and infrastructure may be oriented to either encourage or discourage entrepreneurial activities. Evidence shows that most academic institutions in Canada and the United Kingdom are consciously attempting to do the former by increasing resources allocated to technology transfer activities. (4) Another bridge between the political and moral economies of science is provided via government funding regimes. Economically oriented activities are directly supported by funding programs that require industry-university collaboration, matching funds, or the demonstration of economic or social benefit as a condition of funding. Alternately, funding regimes may indirectly encourage commercial activities through specific funding programs and selection criteria. In both Canada and the United Kingdom, the research councils, which are the government bodies responsible for funding university research, have, over the past two decades, become increasingly concerned with the economic impact of the research they fund. (5) Finally, a connection is created between the political and moral economies of science by use of science indicators (measuring, for instance, the impact of scientific publications or university patenting activity) to gage national economic performance and potential. As a result of this practice, scientific reputations and activities are being directly linked with national performance measures. …
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.
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 | 0,007 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,013 | 0,049 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle