Nutrigenomics, Popular Representations and the Reification of "Race"?
Notice bibliographique
Résumé
I. Introduction The concept of has long been controversial. Not only is it a profoundly socially divisive notion, its relevance to biomedical research community remains contested. Few in scientific community would claim that centuries old, socially constructed categories of race--such as black, white, Asian--have true biological significance. The human species cannot be categorized along clear biological demarcations. Indeed, we humans are a remarkable genetically homogenous lot. And more we learn about subtle genetic variations that make each of us biologically unique, more it seems that social concept of is a biological fiction. (1) That said, there are, no doubt, subtle and identifiable genetic differences between discrete populations based on geographic origin. Understanding these differences can facilitate genetic research and, ultimately, disease treatment and prevention. And an exploration of difference does not lead, inextricably, to social dilemmas. As noted by one scientist: Depending on how we use this information, potential exists to describe simultaneously our similarities and differences without reaffirming old prejudices. (2) But it is easy to slip from a discussion of genetic variation between populations to use of biologically crude and politically and historically complex notion of race. As such, researchers, clinicians and entities that provide genetic services to public must be careful how they communicate genetic information. In this paper, I explore concept of race in context of emerging field of It has been said that the assumption of real genetic markers that distinguish one ethnic group from another is at philosophical heart of nutrigenomics. (3) Given this perspective, might marketing of nutrigenomic services and products facilitate re-legitimization of race as a biological concept? (4) II. Nutrigenomics, Genetics and Race The current value of nutrigenomic testing has been questioned by many, including popular press, (5) some in scientific community, (6) government agencies, (7) and non-governmental organizations. Despite this apprehension, some companies already market nutrigenomic tests directly to public and more will likely follow. (8) The business strategy for these companies varies, but many already offer nutrigenomic testing to public. As suggested on one company's website, aim of testing is to provide personalized health and nutrition recommendations based on an individual's diet, lifestyle and unique genetic profile. (9) The website for this company goes on to suggest that nutrigenomic testing will help public develop a gene-based road map to health. (10) As part of marketing of nutrigenomic testing, it seems likely or even inevitable that race will be used, either explicitly or implicitly, as a marketing tool. (11) The scientific literature that surrounds nutrigenomics often refers to populations from Africa, Asia, and Europe. (12) At least one genetic testing company, DNA Direct, already advertises on their website for testing based on ethnic risk. (13) This is because genetic variations that may cause individuals to metabolize food differently can roughly correspond to broad social categories of race. Most Northern Europeans, for instance, can drink milk while many from Southeast Asian cannot. (14) This kind of geographically based variation can be found in other areas of genetic research, such as pharmacogenomics. (15) Indeed, many of emerging large-scale population studies are specifically designed to identify gene variations within and between sub-populations. (16) It is hoped that this research will lead to an understanding of how members of certain sub-populations may have genetic characteristics relevant to health; be it a predisposition to certain diseases, capacity to respond more effectively to a certain pharmaceutical, or ability to metabolize caffeine in a particular manner. …
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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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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