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Field
Intervention (Public)
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Before
We implement a two-part, individual-level randomized intervention on SAYouth.mobi (in partnership with Harambee) targeting unemployed South African youth (18–35).
1. AI-supported skills elicitation & CV builder (vs. status quo and a static skills-picking form):
Half of participants are offered an AI conversation (embedded in our Compass tool) that helps them surface prior experience (including informal work), translate it into a clearer skills profile, and generate a CV; the other half completes a control online task and proceed with business-as-usual platform resources during the study window. We track clicks and usage from the chatbot and links it provides.
2. Personalized labour-market information (cross-randomized):
Participants are also randomized to one of two concise, personalized messages that provide information on the labour demand of their elicited skills.
• Pull-only (“good-news only”): highlights one of the user’s skills that is above their portfolio average in current vacancy demand.
• Push+Pull (“good-news + bad-news”): shows the same good-news line, plus an added “bad-news” line about the user's skill areas with below-average demand. This isolates whether adding unpleasant facts discourages action despite identical recommended next steps. We hold message length constant across arms.
Design notes and delivery: Recruitment and consent occur on-platform; up to ~4,000 users are enrolled. Messages are delivered in-app and/or by link and are brief, quantitative, and auditable (shares/counts derived from tagged vacancies). Participant incentives (not tied to treatment assignment): participants in both groups receive R30 to complete the online task to offset internet costs; those who complete the phone survey receive extra R50.
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After
We implement a two-part, individual-level randomized intervention on SAYouth.mobi (in partnership with Harambee) targeting unemployed South African youth (18–35).
1. AI-supported skills elicitation & CV builder (vs. status quo and a static skills-picking form):
Half of participants are offered an AI conversation (embedded in our Compass tool) that helps them surface prior experience (including informal work), translate it into a clearer skills profile, and generate a CV; the other half completes a control online task and proceed with business-as-usual platform resources during the study window. We track clicks and usage from the chatbot and links it provides.
2. Personalized labour-market information (cross-randomized):
Participants are also randomized to one of two concise, personalized messages that provide information on the labour demand of their elicited skills.
• Pull-only (“good-news only”): highlights one of the user’s skills that is above their portfolio average in current vacancy demand.
• Push+Pull (“good-news + bad-news”): shows the same good-news line, plus an added “bad-news” line about the user's skill areas with below-average demand. This isolates whether adding unpleasant facts discourages action despite identical recommended next steps.
Design notes and delivery: Recruitment and consent occur on-platform; up to ~4,000 users are enrolled. Messages are delivered in-app and/or by link and are brief, quantitative, and auditable (shares/counts derived from tagged vacancies). Participant incentives (not tied to treatment assignment): participants in both groups receive R40 to complete the online task to offset internet costs; those who complete the phone survey receive extra R60.
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Field
Sample size (or number of clusters) by treatment arms
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Before
2000 treatment, 1800 business-as-usual control, 200 static-form control
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After
2000 treatment, 2000 business-as-usual control, 200 static-form control
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