We measure decision quality before the outcome is known.
The Validated Mind® Research Lab is a decision-intelligence research division of OSQ International, Inc. — operated in affiliation with AI Advisory Group (AIAG), and built around a single thesis: the cognitive systems that validate a decision are knowable, measurable, and deployable with deliberate intention before commitment.
Why we exist
Decision quality has been measured by outcome — long after the decision is gone
For most of the modern history of management science, the quality of a decision has been judged by its result. Markets shift, people surprise us, data is incomplete — so the best a leader could do, the thinking went, was optimize the inputs and evaluate the outcome later. That framing has hardened into the way organizations talk about decisions: post-hoc outcome analysis has become the primary mechanism for improving decision quality.
The cognitive science literature has documented for decades that working backward from outcome to story is itself a systematic source of bias (Baron & Hershey, 1988). The decision was either lucky or unlucky; the reasoning behind it gets remembered to match.
We do not need to wait for the outcome to know whether the decision was validated well. We need to look at the process while it is happening.
The Research Lab exists to make that thesis testable — and the framework that flows from it deployable. The promise is not certainty. The promise is that the cognitive systems doing the validating can be identified, measured, and improved on purpose.
What we're solving for
The validation layer has been invisible — and AI is about to make that catastrophic
Every consequential decision runs through five cognitive validation channels at once. The decision-maker typically feels only the dominant one. This produces the familiar phenomenon of confident decisions that quietly went wrong — the felt sense of having validated, when in fact only one channel was checked.
As decisions move from people to platforms, the cost of that asymmetry compresses dramatically. Whatever logic a leader skipped becomes the logic a system now runs unattended — at scale and at speed. The research community has named the problem; industry has named the problem; what is missing is the layer in between: a structured, measurable account of how validation actually occurs, in real decisions, before commitment.
That is the layer the Research Lab is built to instrument.
Foundations
Each validator is rooted in established neuroscience and decision-science research
The framework is not built from scratch. Each of the five validators sits inside a substantial existing scholarly tradition — Dual-Process Theory, conformity research, naturalistic decision-making, cognitive-developmental moral psychology, and the incentive-sensitization theory of motivation. The contribution of the framework is to organize those traditions inside one operational model.
Validator 1
Verity— Evidence and reason
How we evaluate truth — measurement, replication, hypothesis-testing. Verity is the channel that asks whether a claim can be defended on its own merits.
Brain system
Prefrontal cortex · executive function
Theoretical basis
Dual-Process Theory
Key citations
- — Kahneman & Tversky (1979)
- — Stanovich & West (2000)
- — Stanford Encyclopedia of Philosophy — Scientific Objectivity (2014)
- — Peirce (1877); Chignell (2021) on Kantian fallibilism
Validator 2
Association— Social validation and consensus
How we read the room — whose endorsement matters, what the team or market agrees on, when social signal becomes social proof and when it becomes social pressure.
Brain system
Temporoparietal junction + medial prefrontal cortex · social cognition networks
Theoretical basis
Social Decision Schemes · Conformity research
Key citations
- — Asch (1951, 1956) — line judgment paradigm
- — Bond & Smith (1996) — meta-analysis across 17 countries
- — Frith & Frith (2006) — social brain
- — Hodges & Geyer (2006); Janis (1972) on groupthink
Validator 3
Lived Experience— Pattern and precedent
How we draw on what we have already seen — the felt confidence that comes when a situation matches a prior episode, and the danger when the match is illusory.
Brain system
Hippocampus + medial temporal memory system
Theoretical basis
Recognition-Primed Decision Model · Skill Acquisition · Implicit Learning
Key citations
- — Klein (1998) — Sources of Power
- — Dreyfus & Dreyfus (1986) — skill acquisition stages
- — Hogarth (2001) — kind vs. wicked learning environments
- — Squire & Alvarez (1995); Eichenbaum (2000)
Validator 4
Institutional— Rules, authority, and structure
How we check against the systems we operate inside — policy, precedent, hierarchy, professional standards. Where institutional wisdom protects us, and where it ossifies.
Brain system
Prefrontal–limbic interaction · trust and authority appraisal
Theoretical basis
Cognitive-Developmental Moral Psychology · Regulatory Focus Theory
Key citations
- — Piaget (1932) — heteronomous vs. autonomous morality
- — Kohlberg (1981, 1984) — stages of moral reasoning
- — Rest (1979); Perry (1970)
- — Higgins (1997) — Regulatory Focus Theory
Validator 5
Desire— Motivation and stakes
How wanting shapes what we see. The motivational channel that drives action — and the same channel that quietly bends the evidence toward the preferred outcome.
Brain system
Mesolimbic dopaminergic system · ventral striatum and VTA
Theoretical basis
Incentive-Sensitization Theory · Reward Prediction
Key citations
- — Berridge & Robinson (1998, 2016) — wanting vs. liking
- — Robinson & Berridge (2025) — 30-year retrospective
- — Schultz, Dayan & Montague (1997) — dopamine prediction error
- — Higgins (1997) — promotion focus
An honest note on the neuroscience
Theoretically informed by neuroscience — not derived from it
The brain-system mappings above carry an important methodological caveat. Inferring engagement of a specific cognitive process from activation of a specific brain region is what Poldrack (2006) characterized as reverse inference — and such inferences are not deductively valid. Most brain regions are pluripotent; the default-mode network, for instance, is implicated in autobiographical memory, self-referential thought, and social cognition simultaneously.
The neural references in the framework should therefore be read as anchoring the validator constructs in their most strongly-associated networks — not as claims that any region is exclusively engaged by a single channel. The framework is theoretically informed by neuroscience; it is not yet derived from VALID-specific neuroimaging. The empirical roadmap (below) specifies how that gap will be addressed.
Our distinctive contribution
What we are doing that has not been done before
The validators themselves are not new. Each one rests on a literature decades older than this work. What is new is the operational layer: a way to measure and repeat decision quality at the validation layer — before the outcome is in, and across the contexts where the decision actually occurs.
Measurement at the validation layer — not the outcome layer
Existing decision research evaluates choices by their results. We propose — and operationalize — measurement of the process while it is happening. The instrument captures the validation profile before commitment, not after the regret.
The five integrative zones
Where adjacent validators meet, recognizable psychological constructs appear: Conviction, Values, Identity, Purpose, Trust. Each has a substantial scholarly tradition of its own. Our contribution is recognizing them as the joint outputs of the underlying validation channels — and showing where each fails when those channels fracture.
Context as a tuning mechanism — not an afterthought
Pressure response, team dynamics, and decision repeatability are encoded directly into the scoring. A profile under low pressure that collapses under high stakes reveals a specific developmental target that a single-context measurement would miss entirely.
The human-to-machine translation layer
As AI executes decisions instantly, the absence of explicit decision context creates a continuity risk most decision-support systems do not address. The Decision Validation Engine captures mature human decision logic and translates it into machine-readable parameters — so what scales is validated judgment, not unchecked assumption.
The five integrative zones
Where validators meet, recognizable constructs emerge
The pentagonal geometry of the framework places each validator next to two others. The five interior wedges those pairs form are not decoration — they correspond to constructs with their own deep scholarly traditions. Our contribution is recognizing them as the joint outputs of the underlying channels, and showing where each one fails when those channels fracture.
Desire + Verity
Conviction
Commitment held with sufficient motivation and sufficient evidence to license action. Collapses into motivated reasoning when desire dominates; thins into inert assent when evidence dominates.
Scholarly anchor — James (1896); Peirce (1877); Chignell (2007) on Kant
Verity + Association
Values
The commitments that survive both an evidentiary check and a social validation check. Privately rigorous and publicly defensible.
Scholarly anchor — Schwartz (1992, 2012); Habermas (1990)
Association + Lived Experience
Identity
A narrative self both intelligible to its social context and grounded in the autobiographical record of what one has actually done.
Scholarly anchor — McAdams (1993, 1995, 2001); Erikson (1959); Markus & Kitayama (1991)
Lived Experience + Institutional
Purpose
A forward direction anchored in personal history and located inside a larger structure — a profession, a discipline, a tradition.
Scholarly anchor — Steger et al. (2006); Damon (2008); Frankl (1946 / 1985)
Institutional + Desire
Trust
Motivated acceptance of vulnerability under conditions of incomplete information — within a structurally reliable relationship.
Scholarly anchor — Mayer, Davis & Schoorman (1995); Schoorman, Mayer & Davis (2007)
The empirical program
Five pre-registered studies — designed to be disconfirmed if they should be
The Research Lab operates under five methodological commitments: pre-registration, transparent reporting (including of disconfirming findings), participant consent and GDPR / CCPA-aligned privacy, openness to framework revision based on findings, and named acknowledgment of commercial interest. Each study below has a pre-specified disconfirming outcome — a result that would require the framework to be revised or abandoned.
Study 01
Factor Structure Validation
Pilot sample targeting N ≥ 1,000 employed adults across multiple industries. Exploratory and confirmatory factor analysis tests whether the proposed five-factor structure emerges from the data, against three-, four-, six-, and seven-factor alternatives. The framework is pre-specified to admit revision if the empirical structure differs.
Study 02
Reliability
Internal consistency at α ≥ 0.80 per factor. Test-retest reliability at two-week (r ≥ 0.75) and three-month (r ≥ 0.65) intervals — the lower three-month target reflects the prediction that validation patterns shift modestly with developmental progression.
Study 03
Convergent & Discriminant Validity
Tested against the Rational-Experiential Inventory, Need for Cognition Scale, Big Five Inventory, Meaning in Life Questionnaire, and Genos EI / EQ-i. Pre-specified correlation ranges document where VALID converges with — and diverges from — existing instruments.
Study 04
Predictive Validity
Tested against change-initiative adoption rates, decision-quality outcomes at 90-day follow-up using outcome-anchored rating protocols, and Owner Dependency Index reduction in advisory engagements (target ≥ 25% reduction in successful cases).
Study 05
The 3% Principle
A falsifiable hypothesis — that structured decision validation in mid-market organizations ($1M – $50M annual revenue) recovers approximately three percent of annual revenue through reductions in decision waste, abandoned initiatives, misaligned hires, and avoidable rework. Pre-specified disconfirming outcome: median recovery below 1.5% across N ≥ 25 longitudinal engagements.
Each study is pre-registered before data collection. Disconfirming results are published openly through the Research Lab's Zenodo record and peer-reviewed channels.
Field deployment
The Validated Mind Master Practitioner program
The Validated Mind Master Practitioner (VMMP) program is a certification track for advisors, coaches, consultants, and internal leaders who deploy the VALID™ framework and the Decision Validation Engine in their work. It is also the Research Lab's primary field-data pipeline.
Each certified practitioner operates under a Practitioner IP Agreement that governs their use of the framework and the contribution of de-identified, consent-obtained decision-event data to the central research dataset. Field observations from practitioner engagements feed the empirical program — the patent target is approximately 20,000 decision events across multiple industries. This is how academic decision-science research and consequential field decisions get connected: laboratory paradigms typically lack access to real high-stakes decisions, and practitioner instruments typically lack the methodological infrastructure to generate research-grade data. VMMP is the bridge.
The working paper
The VALID™ Framework — Foundational Working Paper (2026)
A consolidated theoretical and computational account of the framework — six integrated movements covering the neuroscientific foundations, the five within-channel spectrums, the integrative zones, the Decision Validation Engine, the discriminant position against existing frameworks, and the empirical research program. The instrument architecture and method are the subject of U.S. Provisional Patent Application No. 63/839,584.
Status: working paper, precursor to peer-reviewed publication. Numerical values, weight ranges, and performance targets are explicitly identified as theoretical or illustrative pending the pilot studies pre-specified in the empirical program.
Cite as
Donaleski, C. M. (2026). The VALID™ Framework: A Theoretical and Computational Model of Decision Validation. The Validated Mind® Research Lab — Foundational Working Paper.
How this differs from existing frameworks
A meta-framework alongside — not a competitor to — the existing decision sciences
VALID agrees with dual-process theory (Kahneman; Stanovich) that multiple processing modes operate in parallel — but proposes a finer partition than the binary System 1 / System 2 frame.
It treats recognition-primed decision-making (Klein) as a description of one channel's mature operation — the Lived Experience channel at its expert end — inside a broader validation architecture.
It treats the adaptive toolbox (Gigerenzer) as a complementary layer focused on computational strategy — VALID models validation channels, which are sources of confidence in a commitment, not heuristics.
It treats traditional psychometric and emotional-intelligence instruments (MBTI, DiSC, Big Five, Genos EI, EQ-i) as measuring a different layer of human variation — stable individual differences across time. The Decision Validation Engine measures validation logic at the decision event. Trait inventories characterize who a person tends to be across situations; the DVE characterizes how that person actually validates within them. The two are complementary and the DVE can ingest validated trait scores as auxiliary input.
Get involved
Three ways to engage with the Research Lab
Become a Validated Mind Master Practitioner
Deploy the framework in your advisory or coaching practice and contribute de-identified field data to the research record.
Apply
Partner with the Lab
Academic collaborations, industry pilots, replication studies, research data partnerships — the Lab welcomes principled engagement from independent researchers.
Inquire
Start with the book
The Validated Mind: Decision Making in the Age of AI distills the framework for a general audience — full PDF available at no charge.
Read it free
Decisions in the open · weekly
Validation, examined
A near-weekly study of how real-world decisions actually got made — public, observable, deconstructed through the validation that shaped them.
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The Validated Mind® Research Lab — a DBA of OSQ International, Inc., in affiliation with AI Advisory Group (AIAG). VALID™ is a trademark of OSQ International, Inc. The instrument architecture and method are the subject of U.S. Provisional Patent Application No. 63/839,584, filed July 7, 2025. Numerical values, weight ranges, and performance targets cited above are derived from the patent application and are identified as theoretical or illustrative pending the empirical program pre-specified here.
Independent replication by researchers without commercial interest in the framework is welcomed and explicitly invited.