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Record W4393351179

Codévelopper des stratégies pour réduire l'utilisation des antibiotiques : le cas des élevages de poulets au Viêt Nam

2023· preprint· fr· W4393351179 on OpenAlexfundno aff
Chloé Bâtie

Bibliographic record

VenueAgritrop (Cirad) · 2023
Typepreprint
Languagefr
FieldAgricultural and Biological Sciences
TopicLivestock and Poultry Management
Canadian institutionsnot available
FundersAgence Universitaire de la FrancophonieEuropean Commission
KeywordsAntibioticsBusinessBiologyMicrobiology
DOInot available

Abstract

fetched live from OpenAlex

Antibiotic resistance is a global public health concern that could lead to millions of deaths if nothing is done. As a One Health problematic, it needs to be addressed both in human, animal and environmental sectors. Vietnam, with a population of nearly 100 million, is one of the fastest growing economies and demographics in Southeast Asia. The chicken production sector is undergoing a major transformation. The average growth rate of the chicken population is 6% per year and farms are intensifying. Antibiotic misuse and overuse in chicken production is common in Vietnam as products are easily accessible and that the sector is poorly regulated. As a result, many of the bacteria isolated from chicken farms are multi-drug resistant. Strategies exist to tackle antibiotic resistance but they are implemented with difficulties. The objective of this thesis is to co-develop with the stakeholders of the poultry supply chain and of the veterinary drug value chain, strategies to reduce antibiotic use in chicken production in Vietnam. To answer to this objective, we have adopted a transdisciplinary, systemic and participatory approach.After an exploratory study to understand the context in which our study takes place, we have built a typology of antibiotic use practices among the different chicken production systems. We identified three chicken production systems: household, family commercial farms and intensive farms. The decision-making process of farmers varied according to the production system. During the exploratory study, we also identified changes in the regulatory framework and tried to understand how these changes are understood, acknowledged and applied by the stakeholders of the veterinary drug value chain. After mapping the chain and identifying stakeholder’s posture regarding the regulations we have explored the barriers and motivations to implement them. Major barriers included the lack of capacity of the authorities to enforce the regulations, a mismatch between theory and practices, the lack of knowledge on the new regulations and the high proportion of small-scale farms. Because farmers will have no choice but to adapt to the changes in regulations, we then explored how farmers at a local level are dealing with the necessity to reduce antibiotic use. We identified local solutions such as the use of locally-handmade probiotics, knowledge exchange, and organization of farmers in cooperatives to overcome the barriers to ABU reduction. Finally, all the identified barriers and levers were put in to context through the organization of workshops aimed at co-build strategies. The workshops were organized at the local level with stakeholders of the chicken and veterinary value chain. Strategies aiming to improve training and communication on biosecurity and organic production were co-developed.Within this work, we identified barriers and levers to the reduction of antibiotic use in chicken production in Vietnam. Our study emphasizes the need to adopt a systemic and participatory approaches to co-develop local-based solutions using bottom-up approaches. Strategies and solutions must then be disseminated to policy makers for a sustainable change in practice. We also identified the development of quality products value chain in Vietnam that could act as a lever to change of practice but should be done by taking into consideration the most vulnerable stakeholders. Further studies must be conducted in this direction.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.083
GPT teacher head0.288
Teacher spread0.205 · 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 designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

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