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Enregistrement W3006417743 · doi:10.1162/glep_r_00552

<i>Africa’s Gene Revolution: Genetically Modified Crops and the Future of African Agriculture</i>. By Matthew A. Schnurr. 2019. Montreal, QC: McGill-Queen’s Press.

2020· article· en· W3006417743 sur OpenAlexaboutno aff
Robert Paarlberg

Notice bibliographique

RevueGlobal Environmental Politics · 2020
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueAgriculture, Land Use, Rural Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAgricultureCropFood securityAgricultural biotechnologyAgricultural economicsPolitical scienceEconomicsGeographyBiologyAgronomy

Résumé

récupéré en direct d'OpenAlex

Matthew Schnurr’s book, Africa’s Gene Revolution, stakes out an important position. It argues that genetically modified crops (commonly known as GMOs) have not been widely taken up in Africa because they fail to meet the needs of the numerous smallholder farmers on that continent. GMO crops can deliver benefits on some large-scale commercial farms (operated by white farmers in South Africa), and on some large irrigated farms (cotton farms in Sudan), but for poor smallholder farmers, the seeds are less valuable. For example, GMO cotton seeds protect against the wrong crop pests in Uganda, and they have produced low-quality fibers in Burkina Faso. They are developed and disseminated top-down, by distant researchers who do not understand the social and economic circumstances of poor farmers.Schnurr builds his case from an impressive research effort inside Africa, including more than 125 interviews conducted over a decade with local informants, as well as ranking exercises with more than 200 farmers. The result is a detailed country-by-country, crop-by-crop account, packed with valuable technical and institutional detail. The language is clear and the tone is admirably nonpolemical. The frequently alleged food safety and environmental safety risks associated with GMOs are for the most part not evaluated in the book, in part because the author has concluded that they are “relatively minimal.” Instead, the focus is on whether GMO seeds are “pro-poor,” and the author’s judgment is negative, because the seeds seldom fit the distinct needs and circumstances of smallholder farmers.Missing from Schnurr’s work is an alternative explanation for why GMO crops have failed to spread in Africa, an explanation based on the regulatory actions of African governments. In nearly all of Africa, government regulations have made it illegal for farmers to plant GMO crops. Schnurr may be right about the new seeds being a poor fit to the needs of smallholders, but how can we know, so long as government “biosafety” policies have blocked farmers from even trying the seeds? The only country in sub-Saharan Africa to have fully legalized the planting of any GMO food crops so far has been the Republic of South Africa, and there they have been widely successful.Schnurr ignores this regulatory blockage. In his chapter on rules and regulations, he describes Uganda, Ghana, Nigeria, Malawi, Ethiopia, Mozambique, Swaziland, and Cameroon as “emerging adopters” of GMO crops, yet among these countries, only the governments of Nigeria and Ethiopia have so far approved the commercial planting of any GMO crops at all, and the only crop approved has been cotton, not a food crop. This lack of approval means that food crop producers in all of these countries, along with the rest of the region, are still legally blocked from planting GMO varieties of maize, rice, yams, cassava, or banana. Some African countries do have significant GMO crop research programs (Kenya has been doing research on GMOs since the 1990s, as Schnurr points out), but they have yet to give their farmers permission to grow these crops.Schnurr’s analysis also downplays the source of Africa’s highly precautionary GMO regulations. They were brought in primarily from Europe, through NGOs, foreign assistance agencies, and the United Nations system. Highly precautionary biosafety regulations have kept GMOs out of farm fields in Europe, so it is no surprise that similar regulations copied from Europe would do the same in Africa. Schnurr correctly identifies the African Model Law of the Organization of African Unity (OAU) as an umbrella instrument framing these policies, but he fails to mention that promoting this model law in Africa was a German foreign assistance project. Schnurr discusses Zambia’s rejection of GMO food aid, but little or no attention is given to the role of European NGOs in scaring the Zambians away from the aid. One organization from the United Kingdom, named Farming and Livestock Concern, even told the Zambians that GMO maize might introduce a retrovirus similar to HIV (Paarlberg 2008).While underplaying Europe’s blocking efforts in Africa, Schnurr also exaggerates the promotional efforts made by GMO supporters, such as USAID and the Bill and Melinda Gates Foundation. USAID’s Program for Biosafety Systems (PBS) actually reinforced the risk narratives around GMOs by training African regulators to do separate risk assessments for these seeds. When the Bill and Melinda Gates Foundation launched its Alliance for a Green Revolution in Africa (AGRA), the first board chair, Kofi Anan, specifically excluded GMO crops from the technologies AGRA would develop and promote (Southgate 2007).Schnurr’s book can still be used to good advantage, especially by those with research interests in the case studies. Schnurr’s work on the Insect Resistant Maize and Water Efficient Maize projects, and on cotton in Sudan, Burkina Faso, and South Africa, is well informed and up to date. Yet even here something is missing. When Schnurr concludes that GMO cotton will not work for the kind of smallholder farmers found in Africa, he never mentions that smallholders in China and India have been using Bt cotton widely and successfully for several decades now. Most Bt cotton farmers in India are very small, planting only three to four acres of the crop. Bt cotton spread rapidly in these two countries as soon as government regulators legalized use of the seeds; African farmers in cotton-growing countries like Uganda, Kenya, and Tanzania deserve a similar chance to try the seeds in their own fields.Norman Borlaug, the Nobel Prize–winning scientist who grew up on a small farm in Iowa, and who launched the original green revolution in South Asia in the 1960s, uttered these last words before he passed away: “Take it to the farmer” (Quinn 2010). That would be good advice for Africa today.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,345
Score d'incertitude au seuil0,482

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,007
Tête enseignante GPT0,167
Écart entre enseignants0,160 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

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
Publié2020
Routes d'admission1
Résumé présentoui

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