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Review the assumptions before you buy
Read this first: the decision boundary
This pack is built for Kenyan applicants preparing for legitimate data annotation, AI evaluation or microtask assessments without using leaked tests or client data.
Its practical outcome is: Improve consistency and evidence-based judgment while measuring time, accuracy and realistic net hourly return.
It is a recordkeeping and decision-support system. It does not replace a current official requirement, a signed contract, a lender's terms, or advice from a qualified professional. Prices, eligibility, rules and market access can change. Every material figure should be supported by a dated quotation, transaction record or authoritative source in the workbook's Sources tab.
The operating workflow
- Read the entire instruction before answering
- Separate observable evidence from assumptions
- Record confidence and time
- Score with the rubric only after completing the task
- Repeat paired items to test consistency
- Screen the platform and calculate net pay before sharing data or accepting work
Work in this order. A dashboard result without the underlying records is not evidence. If a step does not apply, mark it not applicable and explain why rather than deleting the control.
Research used in this guide
- Digital labour in Kenya — International Labour Organization
- Ajira Digital Programme — Ministry of Information, Communications and the Digital Economy
- Job scams — US Federal Trade Commission
- Data-protection guidance — Office of the Data Protection Commissioner