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Enregistrement W2937320573 · doi:10.1111/1467-9566.12886

Brosnan, C., Vuolanto, P. and Brodin Danell, J.‐A.Complementary and Alternative Medicine: Knowledge Production and Social Transformation. Palgrave Macmillan. 2018. 337pp. 2 illus. ISBN 978‐3‐319‐73939‐7

2019· article· en· W2937320573 sur OpenAlexaboutno aff
Ellen Stewart

Notice bibliographique

RevueSociology of Health & Illness · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueComplementary and Alternative Medicine Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésChinaSummitBiomedicinePower (physics)SociologyPolitical scienceDelegationSocial sciencePublic relationsLaw

Résumé

récupéré en direct d'OpenAlex

Complementary and alternative medicine (CAM) has been a fertile topic for sociologists of health and illness for decades. It is a field often presented as centring on a conflict between proponents of CAM, and the arrayed infrastructure and agents of ‘conventional’ biomedicine. This valuable collection presents eleven studies which seek to trouble, or at least open up, that long-standing assumption. In their introductory chapter, Brosnan, Vuolanto and Brodin Danell offer an expansive, insightful review of existing literature which should become standard reading for scholars of these issues. They argue that in academic analyses CAM has operated as a ‘signifier of other, broader societal shifts’ and ‘a provocative entity … used to increase or undermine the power of patients and practitioners’ (p2). The editors then make the case for approaches which, instead, examine specific instances of CAM practices as found, avoiding easy assumptions about the homogeneity of therapies within the category. The following 11 chapters take up this challenge, exploring how CAM is assembled and especially evidenced differently through practices in diverse contexts. The editors (themselves an international team) have brought together studies of CAM in the Czech Republic, Finland, China, Brazil, Portugal, Kyrgyzstan, Sweden, Canada, Denmark and the USA. The resulting chapters are eclectic and fascinating to read. For example, Stockelova and Klepal's contribution opens with a description of a peculiar ministerial summit at which Health Ministers of Central and Eastern European countries meet a Chinese delegation promoting traditional Chinese Medicine, amid exhibits at which practitioners ‘could perform diagnosis either by examining your tongue and pulse or by connecting you to their computers’. As well as an intriguing ethnographic vignette in its own right, such description highlights one key theme of the collection, explicating how CAM is assembled transnationally. The chapter from Almeida, Siegel and De Barros enlarges on this theme, comparing how global governance of three therapies has been ‘reinterpreted locally’ in Brazil and Portugal. Another key theme evident across the collection is how evidence for CAM is constructed and mobilised in practice. Ning's ethnographic study of how Traditional Chinese Medicine practitioners employ epistemic hybridity in combining biomedical/scientific and traditional/experiential sources of evidence is an exceptionally lucid explanation of complex conceptual terrain. Elaborating differences between the perspectives of different practitioners within the study, as well as a determined commitment to the validity of different knowledge systems, permit a generous exploration of contemporary challenges in Traditional Chinese Medicine practice within Canadian integrative healthcare. The case for examining knowledge production and application in CAM scholarship is well-made in the introductory chapter, and evidenced through the subsequent chapters. The absence of a concluding chapter means that there is little sense of the collection arriving at a firm position. This is in keeping with the editors’ stated goal of taking the sociological study of CAM in a new direction; a beginning, not an ending. Yet by the end of the collection, I sometimes missed the energy of more passionate contributions to the sociology of CAM. Studies of CAM have often been explicitly positioned precisely because of histories of biomedical failure of particular patients (especially those with chronic and multiple illness) and histories of the exploitation of patients by unscrupulous ‘CAM’ practitioners. The commitment of some chapters to epistemological and ontological symmetry can feel uncomfortable in this highly normative context. For example, Penkala-Gawecka's Actor Network Theory analysis of a ‘miracle bed’ in Kyrgystan emphasises the ‘profound agency’ of the bed in stabilising the network of actors (human and non-human) studied. While I genuinely enjoyed the analysis, the images that stayed with me were instead the dispassionate descriptions of financially strapped retirees saving their small pensions or selling their last cow in the hope of acquiring the bed. In a cover quote, Wahlberg welcomes the collection's ability to ‘look past the polemics’. Undoubtedly we do need to move beyond the ‘CAM wars’ in search of greater insights about both CAM and its ‘conventional’ other: this collection ably makes that case and demonstrates the value of this progression. The challenge which remains is to do this without losing sight of continued vulnerabilities and injustices within the field.

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)0,002
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,998
Score d'incertitude au seuil0,157

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,005
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0040,006
Études des sciences et des technologies0,0020,004
Communication savante0,0070,007
Science ouverte0,0020,002
Intégrité de la recherche0,0030,004
Charge utile insuffisante (le modèle a refusé de juger)0,0470,016

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 Opus0,042
Tête enseignante GPT0,346
Écart entre enseignants0,304 · 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.

Devis d'étudeThéorique ou conceptuel
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
Publié2019
Routes d'admission1
Résumé présentoui

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