• Guide to Causal Mapping
  • Overview
    • What is Causal Map?
    • Videos
    • Support chat
    • Quizzes
    • Selected projects to date
    • License
  • 1: Getting Started
  • Level 1 overview
  • 📚 What is a causal map?
  • 📚 What is causal mapping?
    • Causation - no longer a taboo
  • 📚 Are Causal Map and causal mapping for you?
  • Prerequisites for using the app
    • Signing up
  • Accounts
  • Getting help
    • Tooltips
    • Blue info buttons
    • Help button
    • Support chat
  • Has someone shared a file with you?
  • You want to code your own data?
  • Your first 5 minutes with Causal Map
    • Quick tour of the app
    • Coding a file
      • Multiple statement selector
    • Viewing and analysing a file
      • The Dashboard
      • The other tabs
  • Interactive View
    • Tracing paths
  • Print view
    • Copying your map as a vector image
  • Tables
    • Presets
  • Level 1 quiz
  • 2: Basic Coding
  • Level 2 overview
  • Making your own copy of a file
  • Creating a new file
  • How to upload and update your data – Overview
  • Preparing to code
  • The info panel
    • The memos panel
  • The Coding Panel: creating factors and links
    • Creating links in the app
      • About the factor label dropdown menus
  • Editing factors and links (basic)
  • 📚 Factor labels: introduction
  • 📚 Factor labels: actual facts?
  • 📚 Factor labels: actor-focused
  • 📚 Factor labels: semi-quantitative
    • “Semi-quantitative’ labels
      • Examples of semi-quantitative factors
      • Non-quantitative factors
  • 📚 Factor labels: using flags
  • Level 2 quiz
  • 3: Basic analysis
  • Level 3 overview
  • Analysing a file
    • Background information about filters
  • The Dashboard
  • Tables
    • Features common to all the tables
      • Main controls
      • Search
      • Sorting
  • The Factors table
    • Factor memos
  • The Mentions Table
  • The Links Table
    • Fields
  • The Statements Table
    • Fields
  • The Sources Table
    • Fields
  • The Questions Table
  • The Closed Question Blocks Table
  • The Metrics Table
    • Summary
    • What the metrics mean
  • Level 3 quiz
  • 📚4: Advanced coding
  • Level 4 overview
  • Managing your file: The top menu
    • Sharing files with the Current File Manager
      • Sharing and locking files
      • File memo
    • Making your own copy of a file
    • Saving a file as currently filtered
    • Restoring a previous version of your file
    • Uploading your data
    • Chat about this file
  • Data manager
    • Sources in statements table not in sources table:
    • Links which seem to have quotes which are not actually contained in the corresponding statements:
    • Missing sources in statements table:
    • Sources in sources table not in statements table:
    • Statements in links table not in statements table:
  • Collaborating at Causal Map
    • Overview
      • Details
    • Teams
  • Uploading your data
    • 🧪New unified interface for uploading
    • Importing a simple, wide-format file
      • Adding additional cases with wide-format files
    • Standard format
      • Formatting a Standard Format file: The basics
      • Starting from a Word document
      • Uploading multiple PDFs and word-processing documents (doc, docx, odt)
      • Making a basic statements table by hand
  • Uploading additional data
    • Providing additional data as additional fields in the statements table.
    • Uploading using separate source and question tables
  • Appending and fixing data (“roundtripping”)
    • General principles
    • Downloading a file
    • Uses for roundtripping
    • What if you have merged cells in your Excel file?
  • Importing your data: special cases
    • Importing from other software
      • Exporting for import into kumu.io
      • Exporting for import into NodeXL
    • 🧪Importing existing causal coding (“links only”)
    • Uploading closed question blocks
      • QuIP-specific: Uploading hybrid format data
    • Appending hybrid data
  • Merging files
    • Alternative method
  • Editing factors and links (advanced)
  • 📚 Factor labels: consolidating
    • Consolidating and editing factor labels
      • Merging multiple factors into one
      • QuIP specific: back-chaining
  • 📚 Factor labels: desirable?!
  • 📚 Factor labels: more about flags
    • Flags for bundling factors
    • Intervention Flags
    • Outcome Flags
    • Hanging flags
  • The Factor Editor
    • Summary
    • Editing factor labels in the Factor Editor
    • Merging your factors
    • Split-recoding existing factors: Use the Split checkbox.
    • Advanced editing tips
    • The factor editor sidebar
  • 📚 Simplifying causal maps with hierarchical coding
    • Summary
    • Introduction
    • A factor can’t belong to two different hierarchies
    • Zooming out
      • Zooming out is like making deductions with the ; separator
    • Semi-quantitative formulations work best
    • Higher-level factors are generalisations
      • Don’t mix desirability!
      • Using higher level factors for “Mixed bags”
    • Hierarchical coding as a way of coping with a large number of factors
    • Don’t use a hierarchy when a flag will do
    • Re-usable factor components as flags
  • Hierarchical factors in Causal Map
    • Creating labels
    • Organising your factors using the Factor Editor
    • Additional calculated fields
    • Additional functionality when creating and editing links
      • Quick tails: quickly adding new “daughters” of an existing “mother”
    • Additional functionality when searching for and filtering factors
    • How can I view just the factors where I have applied hierarchical coding?
  • 📚 Coding opposites
    • Summary
    • Combining opposites
      • Two-tone links
      • Filtering
    • Opposites coding within a hierarchy
    • Opposites coding within components of a hierarchy
    • Unpacking opposites
    • 🧪The border colours and how to override them
  • Importing a codebook of factors
  • Creating links (more tips)
    • How the factor dropdowns work
    • Creating more than one link at a time
    • Chaining Links
  • Link memos, flags and hashtags
    • Using memos and hashtags
      • Memos
      • Link flags (aka Hashtags)
  • Ellipses
    • Coding your statements in context: referring to evidence from elsewhere
  • Quickfields
    • Summary
    • Alternative formulations
    • Quickfields are also ordinary flags
    • Syntax
    • More than one quick field
    • Permanence
    • Position in hierarchy
    • Current limitation
    • Quickfields for links
    • Quickfields for factor labels versus ordinary hashtags for links
  • Document coding score
  • 📚 Plain coding
    • Summary
    • What the app does
    • Future
  • Level 4 quiz
  • 5: Advanced analysis
  • Level 5 overview
  • Dashboard (advanced)
    • Using and sharing a view
    • ⭐ Recommended views versus 🤵custom views
    • Complete views versus “Add-ons”
    • To edit the content (filter, tab etc) of an existing view:
    • Applying a view
    • For admins
  • Filters – overview
    • Applying different filters
    • Find factors
      • Searching and filtering factors
    • Find statements, find links
      • Find links
    • Highlight only
    • Remove brackets
    • Excluding factors, links, statements, sources and questions with notcontains and notequals
    • Trace paths
    • Bundle factors
    • Combine opposites
    • Filtering group by group
  • What is the logic behind the Causal Map filters?
    • Keeping it simple
    • The order of the filters with calculated fields
    • Autocorrect
    • Where do these islands come from in my map?
  • Filters: tips
    • Restoring previous filter
  • 📚 Analysis: comparing maps between particular groups
    • Filtering by respondent group
    • Showing distinctive maps for each group
    • Filtering statements and groups for comparisons in Causal Map
    • Percentages
    • Surprise
  • Quickfields: analysis
    • Summary
    • Uses
    • Quickfields are also ordinary flags
    • Hiding quickfields
    • Current limitation
    • 🧪Quickfields for links
  • 📚 Tracing paths
    • Summary
      • How to trace paths
      • Removing unwanted links
  • Continuity and tracing threads
    • Summary
    • Tracing threads (aka tracing continuity)
    • Advanced diagnostic filter: Mark links for continuity (Print View only)
    • Advanced diagnostic filter: Show continuity
      • Summary
      • Showing continuity with arrowtypes
      • Showing continuity with colours
      • More about these metrics
  • Conditional formats
    • Conditional formatting for links
      • 🧪Dashed links
    • Conditional formatting for factors
      • Colour text
      • Label factors
    • Bundle links
    • Colours
      • Fixed colours
      • Changing discrete palettes
    • Calculated fields
      • Links table
      • Factors table
      • When combining opposites
  • Simple formats
    • Fixed colours for all links, factors and factor borders
    • Setting specific colours for links, factors and factor borders
    • Wrap factor/link labels
    • Cluster factors
    • Set print format
      • Layout
  • Smart zooming
  • 📚 Clustering sources
    • Filtered clusters
    • The clustering algorithm
    • Bundling links by cluster
    • Finding many solutions at once
  • Recalculate fields
  • 📚 Interpreting your results
  • Tables - advanced
    • Creating your table
    • Print view
    • Formatting your table
    • Saving your table
  • Top tips on coding
  • Level 5 quiz
  • The rest of the app
  • The Updates tab
  • The File Manager
  • Managing your subscription
  • 📚Spotlights
  • Spotlight
  • 📚 Causal Mapping: Definitions
    • What is a causal map? What is causal mapping?
    • Summary
  • 📚 Causal mapping for evaluators
    • Causal mapping for evaluators
    • Features which causal mapping approaches have in common
      • Causality
      • Modularity
    • Causal maps as a summary of qualitative data analysis of textual causal claims for each link
    • Causal mapping as a form of data collection
    • QuIP as a form of causal mapping
      • QuIP: explanations of changes do not themselves also have to be changes
    • Advantages of causal mapping
      • Induct
      • Discover
      • Distinguish
      • Present
      • Query
      • Quote
      • Reuse
    • When to use Causal Map
  • 📚 Causal Mapping and Outcome Harvesting
  • 📚 Context in causal mapping: how to code it
    • Using context in the Causal Map app
  • 📚 Beware the transitivity trap
    • The transitivity trap
    • Not just a problem for causal mapping
    • Can we mitigate the trap with careful elicitation protocols?
    • Transitivity trap, or identity trap?
  • 📚 Cases, variables and percentages in causal mapping?
  • 📚 Different kinds of question chaining, with QuIP and ParEvo as illustrations
    • Four options with Fixed versus Variable question chaining
    • Single versus multiple
    • Future in past, past in future
    • Closed vs open questions
    • Going both ways: bi-directional chaining
    • Evaluation
  • 📚 How to get to the shadow side: a problem with back-chaining
    • Concert example
    • Football example
    • One solution: pairs of initial questions
    • Solving the deeper problem
    • So what can we do?
      • Counterfactual worlds
      • Best solution?
      • Encoding the results
    • Conclusion
    • Finally …
  • 📚 Strength: Adding additional information like strength of a link in a causal map
  • 📚 The last minute principle
  • 📚 Causal maps, systems maps, what’s the difference? Does it matter?
    • What is the difference between a causal map and a systems map?
    • Are systems maps about systems?
  • 📚 Coding time in causal mapping
    • Temporal features which can emerge without explicit coding of time
    • Temporal information attached to additional data
    • Recording temporal information in causal links
    • Recording temporal information in factor labels
      • Use a hashtag or flag
      • Use components in hierarchical coding
      • Use higher-level temporal components in hierarchical coding
      • But what if factor labels themselves express changes?
    • Lateness
    • Analysing and displaying the results of temporal coding
  • More about coding opposites
    • Reversible?
      • Combining opposites and strengths
    • Graded factors: differences of degree
    • Philosophical discursion: coding with propositions
      • Zero influences.
  • 📚 Puzzles in causal mapping
    • Distinctive Groups
    • Quantity of Evidence
    • Joining rules
    • Does believing that X influences Y mean you have to believe that not-X causes not-Y? Causal mapping and counterfactuals.
    • Homogenity of paths
    • (non-) solution 1)
    • Solution 2)
    • Solution 3)
    • Solution 4)
    • Solution 5)
  • 📚 Is one direction enough?
  • Showcase: how the Causal Map app has been used
    • Reports
      • VOSCUR
      • World Food Programme
      • Power to Change
      • Global Young Academy: Tracing the paths of GYA’s impact
      • IFRC Nepal Meta-evaluation
  • Technical reference
  • Technical reference
  • Video list
  • Conventions
    • Formatting in this guide…
  • Screenshotting your maps
  • FAQs: Causal Map questions and troubleshooting
    • Logging in
    • Setting Up
    • Uploading and tweaking data
    • Coding
    • Known Bugs
    • QuIP questions
    • Downloads
  • 📚 Glossary
    • Generic terminology for causal mapping
  • Filter reference
  • How Causal Map is hosted
  • Reports tab
    • Sample
    • Hierarchy
    • Opposites
    • Rankings
    • Differences - questions
    • Differences - sample
    • Differences - sample
    • Differences - question
    • Hashtags
    • Custom
  • Core tables in Causal Map
    • The main five tables and the most important fields / columns
      • Factors
      • Links
      • Statements
      • Sources
      • Questions
      • Special case: Closed question blocks
  • Medals
  • Using the Advanced Editor to create and edit filters
  • Keyboard shortcuts
    • General
    • Factor Editor and Advanced Editor
      • Line operations
      • Selection
      • Multicursor
      • Go to
      • Find/Replace
      • Folding
      • Other
  • Causal Map functions
  • Causal mapping with Excel
  • Using StorySurvey: for survey editor
    • Explorer
    • Map
    • Project recodes
    • Project settings
    • Project answers
    • Project questions
    • Project recodes ace: The recodes advanced editor
      • Basic idea
  • Features of Causal Map
    • Main features of Causal Map
    • Additional new features in Causal Map 2
  • Recent changes
    • Version 0.85, 1/12/2022
    • Tables
      • Removing unwanted links
    • Quickfields for links
    • Version 0.81, 9/8/2022
      • Importing a simple, wide-format file
      • Bundling links
      • Improved percentage labels when calculating surprise
    • Version 0.80, 10/6/2022
      • Smart zoom
      • Collaboration
      • The Dashboard
      • Reports Tab
      • Document coding score!
      • Copying your map as a vector image
      • Clustering sources
      • Quickfields
      • Plain coding
      • New palettes for conditional formatting
      • Quick tails
      • Search for main drivers and/or outcomes
      • Filtering print view of tables
    • Version 0.78
      • The Gallery
      • Continuity
      • Quickfields
      • Other features
    • Version 0.75, 27/12/2021
      • Print view: exporting and zooming
      • Label links
      • Highlight factors without removing other factors
      • Printout (for example, printout of quotes) option in tables
      • Path tracing
      • Mark links for continuity (Print View only)
      • Show continuity
      • Roundtripping with the statements table
  • 📚Final section
  • Acknowledgements
  • Appendix: Publications and links
    • Publications
    • Presentations
    • Longer blog posts
    • ResearchGate
    • Resources and apps
    • Bibliography of selected causal mapping approaches
  • References
  • Causal Map

Guide to Causal Mapping

📚 Strength: Adding additional information like strength of a link in a causal map

image-20230128222424253

Let’s keep it simple.

Causal mapping involves modelling people’s causal claims and beliefs as links or arrows between factors. In Part 1 we argued that a causal mapping approach is represented first and foremost by sets of rules which say how causal information is encoded by specific features of the elements of the map. In this second Part, we will present some new rules for encoding causal claims within causal maps. We will see that there is no one perfect set of features we can use for encoding all or even a satisfactorily broad selection of all possible causal claims. Even with some quite basic possible features like encoding the “strength” of a causal link, it is not hard to dream up a range of similar but different sets of rules for encoding and manipulating causal maps using this feature. To encode strength of a link, should we use numbers from 0 to 1, or maybe from -1 to +1? If several links point to a factor, should we simply add up the strengths, or use some function which keeps the value of the factor somewhere lower than 1? And so on.

These kinds of problems are common to all attempts to model phenomena. But the problem is particularly acute with causal mapping, especially in causal evidence mapping, where we try to encode many individual claims or beliefs. For example, when viewing actual causal claims we sometimes (but not very often, unless the sources are academics) come across claims about how a set of two or more factors interact to influence another in a way which cannot be captured just by sets of individual links: one of many phenomena sometimes called “non-linear”. For example, “you need fuel AND oxygen AND a spark to get a fire”. The trouble is, are we going to activate a whole new set of conventions and rules just to cope with this minority of causal claims? Probably not.

In practice, we suggest that any one causal map should select an only one approach (only one set of rules for encoding causal ideas with specific features of the map’s elements) and that this approach should be no more complicated than is necessary to encode most of the causal claims. Mixing approaches within a single map is endlessly tiresome and complicated. It is not a good idea to introduce an additional feature (like “C is necessary but not sufficient for E”) just to cope with a minority of causal claims in the map.