A suite of qualitative analysis tools
A computational qualitative analysis method for subjectivity-rich interviews.
CISA employs linguistic discourse analysis and narrative-analytic techniques to help the analyst get to the data that matters quickly — and to view that data through a range of analytical lenses. Detection is automated; the analyst can override any classification by hand. Always vanilla. No data leaves your device.
§ 01 · What CISA is
An analytical toolkit that embodies its methodology
In generic qualitative analysis software, the researcher manually applies theoretical categories — coding “tension” or “identity claim” wherever they judge them to occur. The software stores and retrieves what is coded, but imposes no theoretical structure. CISA operates differently: the theoretical categories are constitutive of the instrument itself (Prevett 2026, § 4).
Detection happens automatically, through explicit rule-based linguistic and narrative analysis. The analyst remains in control: every automatic classification can be overridden, reassigned or annotated by hand. CISA reports; the analyst interprets.
Always vanilla
HTML, CSS, JavaScript only. No external libraries, no build step, no dependencies that change beneath you.
Client-side only
All analysis runs inside your browser. Transcripts never travel to a server. Press F12 to verify there are no outbound calls.
No AI at runtime
AI was used as a building partner during development. The tools you use contain none. Rule-based detection only, with full analyst override.
§ 02 · The flagship
CISA Narrative
CISA Narrative reads a transcript and surfaces the moments where the speaker is actively doing identity work — what the tool calls a critical incident segment. It then maps the structural oppositions inside and across those moments, classifies their affective quality, and lays out the narrative arc of the interview.
A short worked example
From the synthetic transcript “Sarah” in the position paper:
I have this terrible fear about money, about not having enough, about spending too much. But actually, the fear makes me more rational. It forces me to plan everything, to use spreadsheets, to track every penny.
The contrastive pivot — but actually — marks a constraint reframed as a resource. Fear is held simultaneously as debilitating and as functional capability. CISA Narrative tags this as a Constraint – Resource opposition with a Managed affective quality, and links it to other moments in the transcript where the same opposition recurs.
Per-transcript outputs
Four of the views CISA Narrative produces from a single transcript.
Interview narrative arc
All segments in sequence, coloured by affective quality. The bolt mark indicates a structural opposition.
Domain × Affective Quality
How affective quality distributes across life domains. Each cell is clickable in the tool, revealing the underlying interview talk.
Identity structure
A hub–spoke diagram emerges from detection, not from researcher coding. Click any node in the tool to surface the supporting interview talk.
Structural opposition co-occurrence
Which opposition types travel together across the transcript. Edge thickness is co-occurrence count; segment slices show affective quality mix.
Dataset and group-level outputs
Within a single browser session, CISA Narrative builds a Session Collection — a working set of analysed transcripts that stays entirely on your device. From there the tool produces a parallel family of cross-participant and dataset-level views.
Cross-Participant Report
Compares patterns across multiple analyses in the Session Collection — structural oppositions held in common, register distributions, identity-structure shapes.
Longitudinal
For datasets with multiple waves: tracks shifts in opposition repertoires and affective quality for the same participant across time points.
Dataset Explorer
Browses the full collection with filters and lenses — participants on one axis, oppositions or registers on another, with every cell traceable to its source.
Participant Grouping
Creates and compares subgroups within the dataset — by demographics, by analytic feature, or by hand — and reports differences between groups on the same metrics.
CISA Discursive Tensions Analysis
An aggregated cross-participant view of where and how discursive tension concentrates across the dataset, including co-occurrence patterns and dominant register signatures.
Export & share
Per-analysis results and whole Session Collections can be exported as structured files for archiving, sharing with collaborators, or moving between machines.
Every output traces back to evidence
Click a cell, a node, or a slice and the underlying interview talk opens beside it. If automatic detection has misread an extract, the analyst can override the classification — reject it, reassign it, or annotate it. CISA reports detection; the analyst remains the interpreter.
§ 03 · Reading identity tensions
Two axes, kept independent
CISA Narrative tracks identity tension along two axes that the framework deliberately keeps separate.
The first axis is what the speaker is working with — the structural opposition they are holding (X versus NOT-X). The second is how they are voicing it — the affective quality of the talk in that moment, ranging across harmonious, easy, managed, stressed, and critical registers. The same opposition can be carried harmoniously in one moment and critically in another; these are distinct discursive positions, not the same content in different moods.
For Sarah, fear is held simultaneously as constraint and as resource — not a contradiction the analyst must resolve, but a structural opposition the speaker is actively living with. CISA Narrative surfaces such moments, classifies the register in which they are voiced, and shows how the same opposition recurs across the interview at different registers.
§ 04 · The suite
Companion tools and learning resources
CISA Narrative does not stand alone. A short preparation tool gets a transcript into the format the analyser expects, and a learning guide walks newcomers through what the outputs mean.
TranscriptReady
A formatting helper that cleans and standardises interview transcripts before analysis — speaker turns, timestamps, anonymisation placeholders, and the export format CISA Narrative reads.
CISA Narrative Learning Guide
A self-paced, browser-based guide for new users. It walks through detection, the two-axis framework, and how to read every panel the tool produces.
Focus group analyser
An adaptation of CISA detection for multi-speaker data, with cross-speaker positioning and turn-level affective shifts.
Mapping-interview tool
For interview methods that elicit spatial or relational maps from participants — treating the map itself as analysable data alongside the transcript.
Template analysis
For hierarchical template approaches, with longitudinal matrix views, affect-marker highlighting, and full traceability from template node to extract.
§ 05 · The position paper
How CISA was built
The development approach — using AI in the building of the tool but never in its operation — is set out in full in an open-access paper in Forum Qualitative Sozialforschung.
Theory-Operationalising Tool Co-Creation
Prevett, P. (2026). Theory-Operationalising Tool Co-Creation: Building Methodology-Specific Analysis Tools Through Human-AI Collaboration. A Position Statement for Qualitative Research Methodology. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 27(2), Art. 15.
§ 06 · Walkthrough
Short video demo
A guided run-through of CISA Narrative on a short transcript, showing detection, the four main panels, and overriding a classification by hand.
Coming soon. A short recorded walkthrough is in preparation.
CISA is currently in active development. Email pauline.prevett@manchester.ac.uk to learn more or to be notified when the suite moves out of beta.
§ 07 · About and contact
About the developer
Pauline Prevett is a Reader in Education at the University of Manchester, where she leads PhD research training in the School of Environment, Education and Development. She teaches research methods on several postgraduate programmes. Her research focuses on students' financial identity and financial self-efficacy, and on qualitative and mixed methods research methodology.
Get in touch
For licensing enquiries, collaboration, or to learn more about CISA: