Self-Complexity Measurement Specification v2.1

Active project · Contributions welcome

Why this exists

Why a measurement specification?

Self-complexity research has long been limited by inconsistent measurement approaches, making it difficult to compare findings across studies or accumulate knowledge over time.

This specification provides a unified framework with explicit formulas, transparent assumptions, compatibility with legacy methods, and room for new metrics that do not break the broader system.

Transparency
Formulas, assumptions, and interpretation guidance are made explicit.
Compatibility
Legacy metrics are preserved so newer work can remain connected to prior research.
Extensibility
Novel metrics can be added without flattening the system into one scalar score.
Interpretability
Metrics should be understandable enough to inspect, critique, and apply.

Version snapshot

Version 2.1

Includes corrected attributions, full formulas, plain-language interpretations, singleton handling notes, methodological guidance, and references spanning legacy through network-oriented extensions.

Current downloadable file: Markdown specification with citations and lay definitions.

What this covers

Core structure, metrics, and outputs

Core structure
Self-aspects, attributes, temporal mapping, and multi-dimensional ratings.
Metric families
Legacy, component, composite, spatial, connectivity, network, and distributional metrics.
Output layers
Individual metrics, cohort summaries, longitudinal change, and publication-ready outputs.

Metrics overview

What this specification covers

The current specification organizes self-complexity as a profile, not a single score. It preserves foundational measures while opening space for structural, connectivity, and distributional analyses.

Legacy

Scott's H

Structural diversity in trait sorting, with corrected attribution to Scott and continuity with Linville's use in self-complexity research.

Component

Overlap indices

Directed overlap and mean Jaccard support more precise thinking about redundancy and independence among aspects.

Novel

Crystallization

A structural read on how tightly defined identity clusters are within the broader system.

Novel

Spillover Risk

A network-sensitive estimate of how easily strain or activation may travel across connected self-aspects.

Network

Modularity

Captures whether roles form clean clusters or remain entangled in a less differentiated identity graph.

Profile

Identity Strength Index

A multi-dimensional profile designed to summarize differentiation, coherence, balance, integration, commitment, and positivity.

Important: the specification explicitly advises against collapsing this ecosystem into one all-purpose scalar index. Metrics are intended to be interpreted as a profile organized by dimension.

Metric philosophy

Legacy and modern side by side

The framework retains Scott's H, overlap measures, and other familiar anchors so older and newer studies can still talk to each other.

Interpretation

Understandable, not just computable

Each metric family is paired with plain-language interpretation guidance so the system remains inspectable to researchers, students, and collaborators.

Open workflow

Designed for reproducibility

Specifications, browser-based tools, and exportable outputs reduce black-box dependence and make replication more realistic.

Access the full specification

Download the current version

Version 2.1 includes formulas, definitions, citations, layperson-friendly explanations, singleton handling rules, and reporting guidance.

Developed by Sean P. Mullen, PhD · University of Illinois Urbana-Champaign

Download Markdown Back to Resources

A PDF version and version-tracked open-science hub can be added later without changing the page architecture.

How to cite

Use these citations when referencing the specification or platform

Measurement specification
Mullen, S. P. (2026). Self-complexity measurement specification (Version 2.1). Self-Complexity Research Network. https://selfcomplexityresearch.org

Note: This is a living specification. Version numbers should be included when citing.

@misc{mullen2026scspec,
  author       = {Mullen, Sean P.},
  title        = {Self-Complexity Measurement Specification},
  year         = {2026},
  version      = {2.1},
  publisher    = {Self-Complexity Research Network},
  url          = {https://selfcomplexityresearch.org}
}

If you use these tools or metrics in your research, please cite this specification.

Citing the platform
Mullen, S. P. (2026). Everythingist self-space platform and research dashboard. Self-Complexity Research Network. https://selfcomplexityresearch.org

If you use the self-mapping app or research dashboard in your work, please cite the platform.

Methods become infrastructure when others can inspect, cite, and use them.

This specification is part of a broader open-science direction that includes tools, documentation, and future version tracking.

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