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Record W4372294861 · doi:10.1111/dpr.12711

Food sovereignty for health, agriculture, nutrition, and gender equity: Radical implications for Haiti

2023· article· en· W4372294861 on OpenAlexaff
Marylynn Steckley, Joshua Steckley, Walner Osna, Magalie Civil, Steve Sider

Bibliographic record

VenueDevelopment Policy Review · 2023
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsWilfrid Laurier UniversityUniversity of OttawaUniversity of TorontoCarleton University
Fundersnot available
KeywordsFood sovereigntyFood securityFood systemsSovereigntyFood policyEquity (law)PoliticsAgriculturePolitical scienceRight to foodEconomic growthEconomicsGeographyLaw

Abstract

fetched live from OpenAlex

Abstract Motivation Governments usually see food security in terms of the availability of and access to sufficient, nutritious, and culturally appropriate food. Food justice scholars, however, see food production and provisioning, diet, nutrition, and health, and women's role in all of these aspects, as inherently political, resulting from, and intertwined with, history, politics, and economics. In state policy, these complex dynamics are often siphoned into separate ministerial silos—health, gender, land, environment, trade, etc. Food sovereignty—a concept that addresses unequal power relations within food systems at scales from household to nation—is increasingly being incorporated into national policies, particularly in the global south. Haiti has recently introduced food sovereignty into its policy landscape, but the degree to which this inter‐sectoral approach diverges or coalesces with past policies for food security has not been explored. Purpose How does food sovereignty shape policy in ways that differ from conventional food security framings? How would a food sovereignty policy address questions of land, gender, health, trade, and agriculture in ways that differ from past policies? Methods and approach We analyse the content of seven Haitian policies and plans, post‐2010 earthquake, for agricultural development, food trade and tariffs, land and agrarian reform, gender, food preferences and cultures, and health—themes raised by food sovereignty. We explore how well the existing policies and plans correspond to the 2018 National Policy and Strategy for Food Sovereignty, Security and Nutrition in Haiti (Politique et Stratégie Nationales de Souveraineté et Sécurité Alimentaires et de Nutrition en Haïti—PSNSSANH). Findings Haiti's food sovereignty policy diverges significantly from previous policies and plans in the way it brings together related concerns. Specifically, Haiti's food sovereignty policy, in contrast to sectoral plans, focuses on smallholder farming, encourages the production and consumption of traditional foods, and aims to protect domestic food production from competition by imports. It addresses concerns about food safety, particularly aflatoxins in groundnuts. It recognizes the central role of women as farmers, traders of food (Madanm Sara) and guardians of children's diets. The only significant dimension of food sovereignty that is not fully addressed in the PSNSSANH is that of land and its distribution to those who farm it. Policy implications The PSNSSANH offers a new approach to food, connecting aspects of the Haitian food system that have previously been isolated—tariffs and trade, nutrition and health, production and consumption of traditional foods, peasant land tenure, and women food traders. It represents a radical reframing of issues and policies. Food security frameworks based on food sovereignty that recognize the links between farming, diet, and health can lead to visions of diets, landscapes, cultures, and economies very different to those of neoliberal analyses that focus on sectors with too little account of key interactions within food systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.013
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.498
GPT teacher head0.565
Teacher spread0.067 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2023
Admission routes1
Has abstractyes

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