Many standards systems refer to the ILO agreements and conventions on forced labour, and have incorporated them into their standards. However, they’ve traditionally relied almost exclusively on social audits to monitor compliance, resulting in low identification rates even in high-risk areas. For standards to become more effective as tools to eradicate forced labour in certified supply chains, there’s a need to identify new risk-based tools to assess farms where there's a high chance it could be taking place. Owing to the often hidden, entrenched and culture- and region-specific nature of forced labour, new approaches to monitoring compliance need to be rooted in workers’ experiences, drawing on data from professionals at field level who can support the verification process.
Improving detection and remediation of forced labour in agriculture
Introduction
Project details
Project title: Integrating new data to improve risk assessments and detection of forced labour in agricultural supply chains
Lead organisation: Sustainable Agriculture Network (SAN)
Partners: UTZ and Ergon Associates
Duration: November 2017 to December 2018
Lead organisation: Sustainable Agriculture Network (SAN)
Partners: UTZ and Ergon Associates
Duration: November 2017 to December 2018
Forced labour
Risk-based approaches
SAN, Rainforest Alliance and Ergon Associates came together to find new methods of identifying high-risk locations beyond the tools available to auditors.
The organisations wanted to build an evidence base to support standards to better learn about the drivers of forced labour and improve monitoring and remediation practices, with a focus on high-risk farms. First, they developed a methodology to assess vulnerability to forced labour in agricultural supply chains, consisting of a set of indicators, feasible means of measurement, weighting, user information and data sources.
Download project outputs
Report | Forced Labour Literature Review
The ISEAL-funded research project Integrating new data to improve risk assessments and detection of forced labour in agricultural supply chains (2017 – 18) is an attempt to build the evidence base around monitoring and remediating forced labour in agricultural supply chains in order to improve assessment and detection efforts. This document is an internal interim submission and contains:
- A questionnaire and interview protocol for interviews that will be held with UTZ and Sustainable Agriculture Network (SAN) field experts located in the research’s three countries of focus (Guatemala, India, Kenya). The primary purpose of these interviews is to understand how forced labour occurs in these locations and how information on its occurrence can be practically obtained (i.e. which methods or indicators), which will support the development of the methodology.
- A literature review which has provided a contextual basis for interview questions and selected areas of focus for the interviews. This exercise also provides background knowledge on country forced labour risk factors in the three pilot countries and identifies current leading models for detecting and remediating forced labour.
Working paper | Forced Labour - understanding remediation
This briefing was prepared by Ergon Associates to support the ISEAL-funded research project Integrating New Data to Improve Risk Assessments and Detection of Forced Labour in Agricultural Supply Chains. The project seeks to build the evidence base around monitoring and remediating forced labour in agricultural supply chains
Report | Forced Labour - India Country Pilot Methodology
A report produced for the ISEAL Alliance Innovations Fund project “Integrating new data to improve risk assessments and detection of forced labour vulnerability in agricultural supply chains”.
Report | Forced Labour - Guatemala Country Pilot Methodology
This document contains a draft forced labor toolkit for the better detection of forced labour on farms in Guatemala. This effort responds to the need to use new methods to identify high-risk locations including farms and target additional detection efforts beyond the tools currently available within certification systems. This is owed to the hidden and clandestine nature of forced labour which makes it difficult to detect through audits.
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