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Glossary
Causal mapping – overview
Task 1 – Gathering causal mapping data
Task 2 – Causal coding – minimalist style
Task 2 & 3 Key ideas and conventions
Task 3 – Answering questions – General
Task 3 – Answering questions – Individual questions
Causal mapping in evaluation
Causal Mapping as QDA
Causal Map app and alternatives
Deductive coding with AI
Inductive coding with AI
Improving rigour in the use of AI in social science
Qualia
Case studies
Getting philosophical
AI and the wider world
Finally
Causal Map App
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Pages in this chapter
Intro to data collection with Qualia
The seamless workflow from AI interviews to causal map
AI interviewing - beware of sensitive data
AI interviewing - beware of suitability
AI interviewing - the evaluator retains responsibility
AI interviewing has potential - scalability, reach, reproducibility, causality
AI interviewing needs further work
An AI interviewer can successfully gather causal information at scale
CASA
How Qualia copes with different languages
It is possible to gather evidence at scale about program theory and contribution simultaneously - three steps
Our seamless stories workflow in practice
Qualia and data security
Qualia asks about USA problems, again
Step 1 – Conducting the chat interviews
Step 2a Coding the interviews – Constructing a guideline
Step 2b Coding the interviews – Coding
Step 2c Coding the interviews – Clustering
Using AI interviewing - beware of bias
Your interview instructions have to be explicit
🌻 It is possible to gather evidence at scale about program theory and contribution simultaneously - three steps
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