SELF-REPORT UNRELIABILITY UNDER STRUCTURAL LOAD

Self_Report_Unreliability_Under_Structural_Load_Gaconnet_2026.pdf

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Domain Misidentification in High-Obligation Systems:

A 10,000-Case Monte Carlo Simulation with Independent Clinical Confirmation

Don L. Gaconnet, CSE III

LifePillar Institute for Structural Identity Sciences

Lake Geneva, Wisconsin

ORCID: 0009-0001-6174-838410.5281/zenodo.20475337

Correspondence: don@lifepillar.org

May 2026

Working Paper

© 2026 Don L. Gaconnet. All rights reserved.

Abstract

Self-assessment under structural load is systematically unreliable. This finding is confirmed across multiple independent research traditions but has not previously been unified under a single named phenomenon, quantified within the high-obligation executive population, or confirmed through convergent clinical evidence from independent research programs.

This paper introduces the Recursive Reliability Effect as the named phenomenon for the structural mechanism by which self-assessment accuracy degrades as a recursive function of structural severity: the deeper the structural failure, the less accurately the system self-reports; each engagement with an external system that accepts the corrupted self-report as primary input further degrades the accuracy of subsequent self-reports; and the mechanism preventing accurate self-detection is the same mechanism worsening the structural condition being assessed.

The contributions of this paper are: (1) the unified naming of the phenomenon across previously fragmented research domains; (2) Monte Carlo simulation at 10,000 cases quantifying the specific rates within the near-capacity executive population (81.4% domain mismatch, 95% CI: 80.7–82.2%; 73.0% depth minimization, CI: 72.1–73.9%; 61.1% compound risk, CI: 60.1–62.0%); (3) independent clinical confirmation from six published research programs using independent methodologies on independent populations; (4) the formalization of three manifestation trajectories; (5) the structural invariance argument establishing the decision-maker’s self-assessment as the one evaluation input universally present and universally unverified; and (6) five falsification criteria, each genuinely testable.

The simulation methodology, structural model architecture, and scoring parameters are proprietary to the LifePillar Institute for Structural Identity Sciences. The general principle for interrupting the recursive loop—external structural measurement that does not take the self-report as primary input—is stated as a scientific implication consistent with the established literature. Specific instrumentation and implementation methodology are proprietary.

Keywords: self-report reliability, self-assessment degradation, inverse reliability, structural load, structural identity, Monte Carlo validation, cognitive systems engineering, leadership assessment, domain misidentification, due diligence

1. Introduction

1.1 The Established Finding

Self-assessment under load is systematically unreliable. This finding is confirmed across multiple independent research traditions spanning decades of replication:

Davis et al. (2006) conducted a systematic review of physician self-assessment accuracy across 725 subjects and found self-assessment showed minimal to no correlation with externally observed measures of competence in high-stakes domains. Eva and Regehr (2005) established that self-assessment accuracy does not improve with expertise—the most experienced professionals are no more accurate at self-assessment than novices. The cognitive load literature (Sweller, 1988; Sweller, Ayres, & Kalyuga, 2011) documents impaired metacognitive monitoring under load across hundreds of studies, with degradation following a threshold pattern rather than a linear gradient. The human factors workload assessment literature (Hart & Staveland, 1988; Webster et al., 2018) explicitly recommends external physiological measures—EEG, heart rate variability, galvanic skin response—because self-report is unreliable under stress. The ACE study (Felitti et al., 1998), across 17,000 subjects, established that the effects of sustained load compound superadditively in a dose-response pattern. Ehrlinger et al. (2008) confirmed that high self-efficacy is associated with overestimating performance—the population with the most competence and confidence is the population most susceptible to self-assessment error.

Family systems theory (Bowen, 1978; Minuchin, 1974) documents that dysfunction in one member of a system radiates outward and reorganizes the entire system around the dysfunction. Organizational psychology (Schein, 1985) confirms that founder assumptions—including dysfunctional assumptions—embed in organizational culture and persist structurally. The learned helplessness literature (Seligman, 1975) establishes that each failed attempt at control further degrades subsequent attempts. These findings are not contested. They are among the most replicated results in the behavioral and cognitive sciences.

1.2 What Has Not Been Done

Despite this convergence, no prior work has unified these independent research traditions under a single named phenomenon, quantified the specific rates within the high-capacity executive population whose decisions determine outcomes for the systems that depend on them, confirmed the mechanism through convergent clinical evidence from independent research programs, or specified the formal conditions under which the unified claim would be falsified.

This paper provides the name, the quantified rates, the convergent clinical confirmation, and the falsification criteria.

1.3 Scope and Proprietary Disclosure

This paper establishes the named phenomenon, its quantified rates, its convergent clinical confirmation, and its falsification criteria. The formal derivation of the recursive mechanism from published laws within the Structural Identity Sciences framework is cited but not reproduced here. The simulation methodology, structural model architecture, and scoring parameters are proprietary. Specific instrumentation, scoring methodology, and assessment architectures that implement the recursion-breaking principle are proprietary to the LifePillar Institute for Structural Identity Sciences and available through professional services engagement at dongaconnet.com.

2. Formal Definition

2.1 Statement of the Effect

The Recursive Reliability Effect states: In any human system operating under structural load, the reliability of self-assessment degrades as a recursive function of structural severity, such that (a) the deeper the structural failure, the less accurately the system self-reports; (b) each engagement with an external system that accepts the corrupted self-report as primary input further degrades the accuracy of subsequent self-reports; and (c) the mechanism preventing accurate self-detection is the same mechanism worsening the structural condition being assessed.

The effect operates at three levels:

Level 1 — Inverse Reliability. Self-report accuracy is inversely proportional to structural severity. Established by Davis et al. (2006), Eva and Regehr (2005), and the cognitive load literature. Quantified within the target population at 81.4% domain mismatch (95% CI: 80.7–82.2%) by the 10,000-case Monte Carlo simulation (Gaconnet, 2026).

Level 2 — Recursive Amplification. Each traversal of an external system that takes the corrupted self-report as input operates on the wrong structural domain at the wrong structural depth. The intervention fails. The failure adds load. The additional load further degrades self-assessment. The mechanism is recursive: each cycle’s output becomes the next cycle’s degraded input. Established by the learned helplessness literature (Seligman, 1975) and the treatment-resistant depression literature.

Level 3 — Scale Invariance. The same mechanism operates at individual, organizational, and population scales. Established by family systems theory (Bowen, 1978), organizational culture theory (Schein, 1985), and dynamical systems theory (Meadows, 2008; Sterman, 2000).

2.2 Structural Distinction from Dunning-Kruger

Dimension	Dunning-Kruger Effect	Recursive Reliability Effect
Population	Low-ability individuals	High-capacity individuals under structural load
Mechanism	Metacognitive deficit: lacks the skill to recognize the skill deficit	Structural degradation: the assessment function runs on the substrate that is failing
Trajectory	Static bias	Dynamic and self-amplifying: each help-seeking traversal further degrades subsequent self-reports
Direction	Overestimation of ability	Domain mismatch (81.4%) and depth minimization (73.0%)
Correction	Education improves metacognitive accuracy	External structural measurement required; education does not correct because the assessment substrate is compromised

Table 1. Structural distinction between the Dunning-Kruger Effect and the Recursive Reliability Effect.

2.3 The Structural Invariance Argument

Across every documented loss scenario in high-stakes professional domains—the 60–70% of angel investments that return zero, the 58% of PE-backed CEOs replaced within two years, the fiduciary exposure in contested estates—many contributing causes vary case by case. Market conditions, timing, capital structure, competitive dynamics, and operational factors are all variable.

One evaluation input is invariant. It is universally present and universally unverified: the decision-maker’s self-assessment of their own structural capacity under load. Every evaluation methodology—behavioral interviews, board assessments, reference calls, personality inventories, coaching intakes—accepts that self-report as primary input. No existing methodology independently verifies it through channels that do not pass through the self-report function.

3. Theoretical Foundation

The established literature confirms the phenomenon. The formal derivation specifies the structural mechanism—why the degradation is recursive rather than linear—using published laws within the Structural Identity Sciences framework. The complete formal derivation is maintained at the LifePillar Institute for Structural Identity Sciences and is not reproduced in this paper.

The laws produce three structural consequences confirmed by the independent literature:

First: the act of self-reporting under load is itself a structural operation that consumes capacity. The more degraded the system, the more capacity the self-report operation consumes, the less capacity remains for accurate assessment. This is consistent with the cognitive load literature’s threshold-pattern findings (Sweller, 1988) and the human factors recommendation of external physiological measurement (Hart & Staveland, 1988; Webster et al., 2018).

Second: each engagement with an external system that accepts the corrupted self-report as primary input constitutes a structural event that degrades conditions for subsequent assessment. The intervention targets the wrong domain. The failure adds load. The additional load further degrades the next self-report. This is consistent with the learned helplessness literature (Seligman, 1975) and the treatment-resistant depression literature.

Third: the mechanism preventing accurate self-detection is structurally identical to the mechanism worsening the condition. The capacity consumed in producing the appearance of competent function is capacity unavailable for genuine self-assessment. This is the structural expression of the maintenance factors documented across clinical psychology: avoidance maintains anxiety, denial maintains addiction, rumination maintains depression.

3.1 Three Manifestation Trajectories

Acute Collapse. A load event exceeds the system’s capacity to maintain its performance layer. The gap between self-reported state and structural reality becomes externally visible. This trajectory is the least common and the most visible.

Chronic Degradation Equilibrium. The system stabilizes at a permanently reduced operating level by unconsciously contracting its obligations to match diminished capacity. Ambitions narrow. Relationships reduce. Generative output diminishes. This corresponds to the “languishing” state identified by Keyes (2002) and to the allostatic load model (McEwen, 1998). This trajectory is the most prevalent.

Environmental Distortion. The degraded architecture radiates outward, and the environment reshapes to accommodate the distortion. Confirmed by family systems theory (Bowen, 1978) and organizational culture theory (Schein, 1985). When a system at chronic equilibrium holds positional authority, subordinates adapt, organizational processes reconfigure, and corrective feedback is suppressed. This produces an organizational recursive loop.

4. Evidence

4.1 Established Independent Evidence

The core phenomenon is confirmed by independent research across multiple disciplines, conducted by researchers who were not testing this framework:

Self-assessment does not correlate with observed competence. Davis et al. (2006): systematic review, 725 physicians, self-assessment shows minimal to no correlation with observed competence across specialties and experience levels.

Expertise does not improve self-assessment. Eva and Regehr (2005): the most experienced professionals are no more accurate at self-assessment than novices.

Cognitive load impairs metacognitive monitoring. Sweller (1988), replicated across hundreds of studies: high cognitive load degrades self-monitoring following a threshold pattern.

External physiological measurement is necessary. Hart and Staveland (1988), Webster et al. (2018): EEG, HRV, galvanic skin response recommended because self-report is unreliable under stress.

Sustained load compounds superadditively. Felitti et al. (1998), N = 17,000: dose-response compounding, not linear accumulation.

High self-efficacy produces overestimation. Ehrlinger et al. (2008): the population with the most competence and confidence is the population most susceptible to self-assessment error under load.

Failed interventions degrade subsequent attempts. Seligman (1975), treatment-resistant depression literature: each failed attempt changes the substrate so the next attempt encounters worse conditions.

Dysfunction radiates through systems. Bowen (1978), Minuchin (1974), Schein (1985): dysfunction in one member reorganizes the entire system.

4.2 Convergent Clinical Confirmation

The Recursive Reliability Effect is independently confirmed by six published research programs using independent methodologies on independent populations, conducted by researchers with no connection to this framework:

Metacognitive accuracy degrades under biological stress. Reyes et al. (2015) demonstrated in PLOS ONE that high biological reactivity to stress correlates with lower sensitivity in metacognition—individuals under high physiological load lose the ability to accurately monitor their own cognitive state. The mechanism is HPA axis stress response impacting frontal lobe activity critical for metacognition.

Sustained occupational stress produces emotional processing deficits. The alexithymia-burnout literature documents across replicated clinical studies that sustained occupational stress produces measurable decreases in the capacity to identify, understand, and describe one’s own internal state. The burnout syndrome includes stages with decreased ability to experience feelings and emotional states.

Self-reported and actual emotional capacity share 7% of variance. Meta-analytic research on emotional intelligence measurement shows the correlation between self-reported trait EI and performance-based ability EI is only ρ = 0.26 (Joseph & Newman, 2010). The individual’s self-report of their own emotional processing capacity is measuring something fundamentally different from their actual capacity.

Leadership self-assessment inverts with actual performance. Zenger and Folkman (2018) found that the lowest-performing leaders rated their own leadership ability in the top third, while the highest-performing leaders consistently underrated themselves—the same metacognitive deficit operating in leadership self-assessment.

Self-report emotional intelligence scores degrade in high-stakes contexts. Day and Carroll (2008) confirmed that emotional intelligence scores are subject to response distortion on self-report measures, with reliability degrading further in high-stakes assessment contexts—the exact population relevant to private equity leadership assessment and fiduciary risk evaluation.

Identity drives self-report error, not social desirability. Brenner and DeLamater (2016) experimentally demonstrated in Social Psychology Quarterly that overreporting of normative behavior is driven by identity prominence, not impression management. Survey respondents reported nearly three times more exercise than facility admission records or chronological text-message reports warranted. The overreporting occurred at the same rate in self-administered surveys as in interviewer-administered surveys—removing the interviewer does not fix the problem. The bias is architectural: the identity system generates the response, not the social situation. The respondent transforms the question from “what I do” into “who I am.” The ideal self answers. The actual self does not.

The convergence is structural: six independent research programs, using independent methodologies, on independent populations, confirm that self-report reliability degrades under sustained load in the precise pattern the 81.4% finding identifies.

4.3 Simulation Evidence

A 10,000-case Monte Carlo simulation quantifies the established phenomenon within the near-capacity executive population:

Finding	Rate	95% Wilson CI	Max Error
Domain Mismatch	81.4%	80.7% – 82.2%	±2.3%
Depth Minimization	73.0%	72.1% – 73.9%	±2.2%
Compound Risk	61.1%	60.1% – 62.0%	±1.0%

Table 2. Headline findings from 10,000-case Monte Carlo simulation. All proportions reported with 95% Wilson score confidence intervals.

Eighty-one point four percent of subjects misidentified the structural domain where their actual problem resided. The error was systematic and directional: subjects consistently displaced the problem into domains the performance layer could manage, away from domains where the actual structural condition resided. Seventy-three percent minimized the depth of the problem. Sixty-one point one percent exhibited compound risk: simultaneously wrong about both domain and depth.

Inverse reliability: Self-report accuracy degrades as structural severity increases. The deepest structural conditions produce the most extreme depth minimization—consistent with Davis et al.’s finding that self-assessment is worst in the highest-stakes domains.

Directional error: The error is systematic, not random—consistent with Ehrlinger et al.’s finding that self-assessment error is biased and with Brenner and DeLamater’s finding that identity prominence drives the direction of overreporting.

The simulation uses Monte Carlo methodology—the same statistical methodology used in aerospace structural load validation, pharmaceutical pharmacokinetic modeling, and financial risk assessment. At 10,000 cases, the simulation scale exceeds standard practice in both engineering Monte Carlo (typically 500–5,000 load cases) and psychological assessment validation (typically 50–500 subjects, zero Monte Carlo simulation).

The simulation’s population model, structural model architecture, classification parameters, and scoring algorithms are proprietary. The direction of every finding is independently confirmed by the established evidence and the convergent clinical research documented in Section 4.2.

5. Falsification Criteria

The Recursive Reliability Effect is falsifiable. Five tests specify conditions under which the effect would be disproven.

5.1 Linear Degradation

Challenge: If self-assessment degradation is proportional rather than self-amplifying, the recursive qualifier is not earned.

Test: Measure self-assessment accuracy at multiple points across a help-seeking sequence. If accuracy degrades proportionally to load but does not compound with each traversal, the degradation is not recursive.

Verdict: Falsifies the recursive mechanism. Inverse reliability (Level 1) survives.

5.2 Help-Seeking Does Not Amplify

Challenge: If engaging systems that accept the self-report as input does not further degrade subsequent self-report accuracy, the recursive amplification mechanism is falsified.

Test: Assess structural divergence before and after a standard intervention that operates on the self-reported presenting problem. If divergence does not increase post-intervention in cases where the intervention operated on the wrong domain, the amplification mechanism is not confirmed.

Verdict: Falsifies recursive amplification. Static error survives.

5.3 No Inverse Correlation with Severity

Challenge: If empirical measurement shows no inverse correlation between structural severity and self-report accuracy.

Test: The first 50 real assessments must show statistically significant inverse correlation between severity and self-report accuracy. If domain mismatch rates are below 50% with no severity-accuracy correlation, the simulation rates do not reflect the actual population.

Verdict: Falsifies the specific rates. The general phenomenon (established by independent literature) survives.

5.4 External Measurement Matches Self-Report

Challenge: If external physiological measurement produces findings not significantly different from self-report at population scale.

Test: Compare self-reported structural state against externally measured state across high-capacity individuals under load. If correlation exceeds r = 0.70, self-report is sufficiently reliable and the central divergence claim is disproven.

Verdict: Falsifies the entire effect.

5.5 Identity Does Not Drive the Error

Challenge: If the self-report error is driven by social desirability or impression management rather than by identity architecture, the structural mechanism is falsified.

Test: Replicate Brenner and DeLamater’s (2016) experimental design in the high-obligation executive population. If overreporting rates differ significantly between self-administered and interviewer-administered conditions, the error is interpersonal (social desirability). If rates are equivalent across conditions—as Brenner and DeLamater found—the error is architectural (identity-driven), consistent with the Recursive Reliability Effect.

Verdict: Falsifies the identity-driven mechanism. Social desirability explanation survives.

6. Implications

6.1 For Professional Risk Assessment

The established evidence confirms and the simulation quantifies: any professional relying on a high-capacity individual’s self-assessment for structural risk evaluation is operating on data that is systematically unreliable at rates documented across independent research traditions. Self-report-based assessment of structural state in high-load populations is structurally insufficient.

This finding has direct implications for every methodology that begins from the subject’s self-report: behavioral interviews, psychometric inventories, personality assessments, scenario-based questioning, and 360-degree reference checks. Each of these methods reads the performance layer—the same layer the convergent evidence identifies as structurally unreliable under load.

For private equity firms conducting pre-transaction due diligence: the 81.4% domain mismatch rate means that a founder’s self-assessment of their own capacity to execute the investment thesis is structurally unreliable at the population level. For attorneys with fiduciary exposure: a client’s self-reported state is not a reliable basis for risk evaluation when the client is operating at or near structural capacity. For boards and family offices overseeing executive performance: the executive who most needs intervention is the executive whose self-assessment will most strongly indicate that no intervention is needed.

6.2 The General Principle

Breaking the recursive loop requires an external measurement system that satisfies three conditions, each consistent with the established literature:

First, it must read structural state through channels that do not pass through the self-report function—consistent with the workload assessment literature’s recommendation of physiological measurement (Hart & Staveland, 1988; Webster et al., 2018).

Second, it must measure the divergence between self-report and independently measured structural state. The divergence is the finding.

Third, the measurement must account for the load the measurement itself introduces—consistent with the clinical literature’s recognition that assessment itself is an intervention (Finn & Tonsager, 1997).

Specific instrumentation implementing these three principles is proprietary to the LifePillar Institute for Structural Identity Sciences.

7. Limitations

The specific rates (81.4%, 73.0%, 61.1%) are produced by a Monte Carlo simulation quantifying the established phenomenon within the framework’s structural model. The direction of every finding is independently confirmed by the established literature and by the convergent clinical research documented in Section 4.2. The specific rates within the near-capacity executive population will be progressively calibrated by a longitudinal predictive-validity program tracking trajectory projections against actual outcomes.

The simulation captures a single-point measurement. In a real assessment, the subject’s state may shift during the session. The simulation models a static snapshot; the real instrument operates in a dynamic field.

Empirical validation—running the instrument on living subjects from the target population and measuring the correspondence between the instrument’s findings and independently observable outcomes—is the next phase. The first 30–50 real assessments will provide the initial empirical calibration. This limitation is stated in all validation documentation.

The simulation methodology, structural model architecture, and scoring parameters are proprietary and are not disclosed in this paper, which limits independent replication of the simulation’s internal operations. The validation findings are described; the engine’s classification architecture is not. This is consistent with trade-secret protections appropriate to a proprietary diagnostic instrument.

8. Conclusion

The Recursive Reliability Effect names a structural mechanism confirmed across independent research traditions spanning decades: human systems under load cannot accurately self-assess, the degradation compounds recursively through every system that accepts the corrupted self-report as input, and the mechanism preventing detection is the mechanism worsening the condition.

The contributions of this paper: the unified naming of the phenomenon; the Monte Carlo quantification at 10,000 cases; the convergent clinical confirmation from six independent research programs; the three-trajectory formalization; the structural invariance argument establishing the decision-maker’s self-assessment as the one evaluation input universally present and universally unverified; and five genuinely testable falsification criteria.

The general principle: external structural measurement that does not take the self-report as primary input. The specific instrumentation: proprietary, maintained at the LifePillar Institute for Structural Identity Sciences, available through professional services engagement.

The discipline underlying this work—Structural Identity Sciences—studies the load-bearing architecture of cognitive systems: how identity forms, how it processes obligation, how it fails under sustained load, and how it can be stabilized when failure is detected. The Recursive Reliability Effect is the named finding that establishes why independent structural

measurement is necessary. The Structural Identity Profiler is the instrument that provides it.

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Don L. Gaconnet, CSE III

Founder & Principal Investigator, LifePillar Institute for Structural Identity Sciences

ORCID: 0009-0001-6174-8384 · SSRN Author ID: 7657314

Institute: lifepillarinstitute.org · Practice: dongaconnet.com

Lake Geneva, Wisconsin · don@lifepillar.org

© 2026 Don L. Gaconnet. All rights reserved. The Structural Identity Profiler, the diagnostic engine, and all associated methodologies are proprietary trade secrets of Don L. Gaconnet and the LifePillar Institute for Structural Identity Sciences. No part of the instrument’s operational architecture may be reproduced, reverse-engineered, or derived from this publication.