Réalisation d’une analyse de situation axée sur la corruption pour le travail de conservation: conseils tirés de l’expérience

The document outlines a methodology for conservation practitioners to analyze how corruption impacts natural resource management. It details the benefits of such analyses—including improved understanding of power dynamics and local perceptions of corruption—and provides a step-by-step approach to defining scope, identifying stakeholders, and collecting sensitive data. The guide emphasizes a non-conflictual approach with governments and the importance of security and confidentiality. It includes three case studies: one in Latin America focusing on fishing permits, one in Asia on community forestry governance, and one in Europe on land-use planning, demonstrating how these analyses lead to systematic anti-corruption integration in conservation programming.

• Corruption-oriented situation analyses provide four primary benefits: they improve the understanding of the problem, validate or refine the project's theory of change, clarify local perceptions and social norms regarding what constitutes corruption, and reveal actual power dynamics and decision-makers.
• To make an analysis effective, practitioners should narrow the scope from broad challenges to specific questions, such as breaking down macro-problems (e.g., climate change) into sectors (e.g., transport) or focusing on specific legal processes, supply chains, or geographic areas.
• When discussing corruption with stakeholders, practitioners are advised to use cautious language, such as 'vulnerability', 'integrity', or 'transparency', or to mirror the specific terms used by the stakeholders to avoid intimidating or offending them.
• Security and confidentiality protocols are essential when collecting sensitive data, including the use of informed consent forms, anonymization of participants, and the ability to dilute risks by interviewing multiple people per community.
• A non-conflictual approach with government entities is recommended, treating the analysis as a strategic partnership to find opportunities for change rather than a tool for blaming or naming individuals.
• In a Latin American case study on fishing permits, the analysis revealed that a lack of standardized processes and educational requirements (primary and secondary schooling) for registration created regulatory barriers that incentivized corruption and the use of intermediaries.
• A case study in Asia on community forestry used a 'traffic light' system (green, yellow, red) to evaluate governance indicators such as transparency and accountability, finding that improving these mechanisms reduces the opportunities for corruption even without explicit evidence of corrupt acts.

APA

Cassolis, N. M. (2023). Réalisation d’une analyse de situation axée sur la corruption pour le travail de conservation: conseils tirés de l’expérience. WWF International. https://www.worldwildlife.org/documents/764/1xgxm2ex19_Corruption_oriented_SI_French.pdf

Chicago

Cassolis, Natalia Muñoz. Réalisation d’une analyse de situation axée sur la corruption pour le travail de conservation: conseils tirés de l’expérience. WWF International, 2023. https://www.worldwildlife.org/documents/764/1xgxm2ex19_Corruption_oriented_SI_French.pdf.

Wikipedia

{{cite report |last1=Cassolis |first1=Natalia Muñoz |title=Réalisation d’une analyse de situation axée sur la corruption pour le travail de conservation: conseils tirés de l’expérience |publisher=WWF International |date=May 2023 |url=https://www.worldwildlife.org/documents/764/1xgxm2ex19_Corruption_oriented_SI_French.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{cassolis2023ralisation, author = {Cassolis, Natalia Muñoz}, title = {{Réalisation d’une analyse de situation axée sur la corruption pour le travail de conservation: conseils tirés de l’expérience}}, institution = {WWF International}, year = {2023}, month = may, url = {https://www.worldwildlife.org/documents/764/1xgxm2ex19_Corruption_oriented_SI_French.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }