R0007/2026-03-19/C001 — Assessment

Research	R0007 — AI Made Everyone Faster
Run	2026-03-19
Claim	C001

BLUF

The core study parameters (five studies, 198 samples, 633,263 individuals, power-law distribution finding) are independently confirmed by multiple authoritative sources. The specific output concentration percentages (top decile = ~30%, top quartile > 50%) are plausible implications of a Paretian distribution but could not be verified as directly reported findings from the paper.

Probability

Rating: Likely (55-80%)

Confidence in assessment: Medium

Confidence rationale: High confidence in the study parameters and power-law finding (almost certain). Lower confidence in the specific output concentration figures because no secondary source reproduces these exact percentages. The compound nature of the claim requires both parts to be accurate for the claim as a whole to be "accurate as stated."

Reasoning Chain

1. Multiple independent academic databases (Semantic Scholar, Wiley, ERIC, PsycNET) confirm O'Boyle and Aguinis (2012) conducted five studies with 198 samples and 633,263 individuals [SRC01-E01, High, High].
2. The populations studied (researchers, entertainers, politicians, athletes) are consistently reported across all sources [SRC01-E01, High, High].
3. The finding that individual performance follows a Paretian (power-law) rather than normal distribution is the paper's central finding, confirmed across all sources [SRC01-E01, High, High].
4. The specific output concentration figures (30% for top decile, >50% for top quartile) could not be located in any secondary source or summary [SRC01-E02, High, High].
5. These figures are mathematically plausible for a Paretian distribution and consistent with the paper's thesis, but may be derived interpretations rather than directly reported findings.
6. JUDGMENT: The claim is substantially correct in its factual claims but the specific percentages may be approximations or calculations derived from the distribution parameters.

Evidence Base Summary

Source	Description	Reliability	Relevance	Key Finding
SRC01	O'Boyle & Aguinis (2012) - multiple databases	High	High	Study parameters confirmed; output percentages not found in secondary sources

Collection Synthesis

Dimension	Assessment
Evidence quality	Robust — multiple independent academic databases confirm core findings
Source agreement	High — all sources agree on study parameters and power-law finding
Source independence	Medium — all secondary sources reference the same primary paper
Outliers	None for core findings; output concentration figures are the gap

Detail

The evidence strongly supports the study parameters and the power-law finding. The paper has been widely cited (1000+ citations) and its methodology has been both praised and challenged (e.g., Beck et al. 2014 argued measurement characteristics play a role), but the core finding of non-normal distributions has been broadly accepted. The output concentration figures are mathematically consistent with a power-law distribution but their specific values could not be traced to the original paper through available sources.

Gaps

Missing Evidence	Impact on Assessment
Full text of original paper	Cannot verify whether 30%/50% figures are directly reported or derived
Specific Pareto exponent values	Would allow independent calculation of output concentration

Researcher Bias Check

Declared biases: None declared in researcher profile (not provided).

Influence assessment: The claim presents the study favorably, which is consistent with using it as supporting evidence for an argument about performance distribution. The specific output concentration figures add rhetorical force; if they are approximations rather than exact findings, this represents a minor accuracy concern.

Cross-References

Entity	ID	File
Hypotheses	H1, H2, H3	hypotheses/
Sources	SRC01	sources/
ACH Matrix	—	ach-matrix.md
Self-Audit	—	self-audit.md