💐🌸🌹🌻🪻Causal mapping:a Garden of Ideas#
Some brief one-page bullet-point summaries of some of our key published papers. Enjoy.
Some essential terminology for causal mapping.
This chapter is a new set of working papers about causal mapping.
What is causal mapping? What are its strengths and weaknesses? How does a causal map differ from a systems diagram? This chapter has some answers.
At Causal Map we are relatively agnostic about data collection. We are most interested in causal evidence and beliefs derived from different sources.
In this chapter we present some of key general principles about how to do causal mapping which we at Causal Map Ltd (and, most of the time, at BathSDR) have adopted.
Causal coding is fascinating but can take a lot of time. Using AI to help you is pretty easy, but there are still quite a few things to think about, as we will explain in this chapter.
In the previous chapter we introduced minimalist causal coding:
The fundamental output of causal mapping is a database of causal links. If there are not too many links, this database can be visualised "as-is" in the form of a causal map or network. But usually there are too many links for this to be very useful, so we apply filters.
Because the output is a structured network, we can apply a range of queries to explore the data. This gives us a library of pre-existing approaches to ask practical questions about the causal landscape described by the participants.
Causal mapping has been used in many different fields. In this chapter we look at how it can be applied in evaluation; its strengths and weaknesses.
Causal mapping is also a kind of Qualitative Data Analysis (QDQ). How does that even work? This chapter explains.
This guide shows how to create a simple causal map in Kumu.io using a spreadsheet. It includes:
How can we improve rigour and even reproducibility when using AI in social science? This chapter suggests some answers.
In this chapter we look at some examples of specific workflows in causal mapping, mostly illustrated with the Causal Map app. It's work in progress, we only have a couple of pages at this point.
Here is the complete reference guide for the Qualitative Causal Parser (QCP v1.0).
2025-12-10 Here are some examples of work with Causal Map and causal mapping, and also with Qualia interviews.
This chapter explains how individual consultants and agencies can include Causal Map and/or Qualia in their next bid.
Some thoughts...
Here are some thoughts from a couple of years ago when genAI first hit us, plus some thoughts about where we are going with it.
, "Evidence gives stories substance, :: but stories give evidence meaning," (https://assessmentinstitute.indianapolis.iu.edu/overview/institute-files/2021-institute/handouts-wednesday-2021/22P_jankowski_handout.pdf)
Licenses, how to cite Causal Map, and a bibliography.
Question for Step 3 - can automated causal mapping help answer evaluation questions?: An overview map was produced which included over 40% of the causal claims identified within the transcripts, using just 11 relatively broad factor labels.