Appendix C: Characteristics of monitoring agents

Granular demographic information on monitoring agents was available for this review only for ICI implemented CLMRS in Côte d’Ivoire. This information was merged with the interview data collected in order to understand how the profiles of monitoring agents relate to the interview outcomes. In the ICI CLMRS data base, we have basic demographic information, with varying detail, of 2’246 community-based agents in Côte d’Ivoire who have been hired and trained for child labour data collection under the CLMRS.

What information is available about children in child labour?

To understand from the data how different CLMRS features and modalities affect a system’s outcomes and impacts, ICI requested CLMRS implementers to share anonymized extracts from child labour monitoring data, disaggregated at the child level. Four companies implementing CLMRS shared disaggregated data points from five different projects in Ghana and Côte d’Ivoire. These were compiled into one data set together with data from the ICI CLMRS data base from 7 different projects.

Appendix D: Stopping children from engaging in hazardous child labour – additional results

Table 1: Marginal effects from logit regression of whether a child stopped doing hazardous work on context factors at child, household and community level.

Variables

(1)

y1

(2)

y1

(3)

y1

(4)

y1

Child's age

-0.0023

(0.0015)

For this review, complete records of children, households and communities benefitting from different types of support to address and prevent child labour were available only from the ICI implemented CLMRS in Côte d’Ivoire. This section presents and discusses some figures on remediation given to children identified in child labour under the CLMRS, as a background for the analysis of remediation effectiveness (section xx of the report).

Table A1: Overview of the 15 projects reviewed in this report

Quelle est la probabilité que les enfants travailleurs identifiés par le SSRTE cessent de travailler ?

Cette section examine la probabilité d’identifier des enfants astreints au travail des enfants par des visites d’observation. Elle étudie la manière dont différents éléments de la conception et de la mise en œuvre du système – y compris qui réalise les visites d’observation, quand, où, et comment – influencent la probabilité qu’un système identifie les cas de travail des enfants, pour que ces enfants puissent, par la suite, bénéficier d’un soutien.

Comment les taux d’identification du travail des enfants varient-ils en fonction des projets ?