Kaal claims by topic: research-methods, page 2

236 atomic, individually citable claims from the published work of Wulf A. Kaal tagged research-methods.

  1. The unanimity result is consistent with reduced cascade behavior but does not uniquely identify that mechanism. 2026
  2. The Article claims only the effects observed in the disclosed research setting; whether they persist, amplify, or invert at production scale is an open question. 2026
  3. Formal objects are therefore linked to named observables without treating code presence as proof of economic effect. 2026
  4. A null can discipline a condition, but cannot by itself uniquely identify a mechanism. 2026
  5. H1 asks whether output quality differs under the joint substrate treatment on a properly matched estimand. 2026
  6. H2 asks the narrower and testable information question: whether reputation adds out-of-sample predictive content beyond observed task outcomes. 2026
  7. Verification does not eliminate asymmetry, because the cohort’s aggregate judgment is itself an estimator with finite variance, and Part VI.C reports a first measurement of exactly how wrong the naive estimator can be. 2026
  8. No single downstream metric uniquely identifies an architectural cause. 2026
  9. Mechanism-specific attribution requires ablation, mediation, or component randomization. 2026
  10. The distinction is a classification, not proof that one arrangement universally displaces the other. 2026
  11. The strict matched analysis must preserve agent, task, and model binding across conditions. 2026
  12. Any broader comparison with changed bindings is a separate, partially matched estimand and must be reported as such. 2026
  13. E2B asks whether a population operating under the substrate can carry state across generations and whether selection produces a trajectory distinguishable from drift. 2026
  14. First, computational activity persisted across a completed generation boundary and continued into the next generation. 2026
  15. Second, the registered selection rule produced a real lineage transition. 2026
  16. The record binds outcomes to generation, lineage, fitness, survival, parentage, reputation consequences, adjudication behavior, and execution timing without requiring public disclosure of the private apparatus. 2026
  17. Under the registered first-exposure estimator, the selection trajectory has an aggregate slope of 0.0685, with an uncertainty interval from -0.0568 to 0.2020. 2026
  18. The random-survival trajectory has an aggregate slope of 0.0419, with an interval from -0.0764 to 0.1768. 2026
  19. The descriptive slope difference is approximately 0.0266 in favor of selection. 2026
  20. The active generation is incomplete, and the checkpoint does not yet support a paired confirmatory interval. 2026
  21. The current evidence establishes endogenous selection inside an externally provisioned experiment. 2026
  22. The present system therefore does not demonstrate autonomous economic persistence. 2026
  23. They do not establish a treatment effect because the information environment was defective and the diagnostic was regraded after execution. 2026
  24. Until that reconciliation and independent verification occur, the estimates in this Part remain interim. 2026
  25. Membership in the sovereign local agent runtime class turns on four testable properties: user-controlled execution, user-held state, heterogeneous composition, and machine-to-machine settlement. 2026
  26. Whether execution occurs on user-controlled hardware is tested by disconnecting the machine from the network and checking that the capability is retained; systems that degrade to nothing when isolated are remote services with a local presentation layer. 2026
  27. The true constraint on scale for sovereign local agent runtimes is coordination cost, which is invisible in throughput, latency, and token-cost benchmarks that measure the performance of composition but not the cost of arranging it. 2026
  28. Evaluation must derive from observed results under stated conditions, be specific to context, and be costly to manipulate, which excludes self-declared capability, averaged scores across incommensurable tasks, and most engagement metrics. 2026
  29. Requirements stated now, against systems still under construction, remain testable; requirements stated later become postmortems. 2026
  30. The paper's claims were stress-tested in a nineteen-round adversarial protocol in which three frontier language models, under the author's direction, alternately attempted to identify counterexamples, algebraic errors, and overstatements; the surviving statements are those neither system broke. 2026
  31. The dominance result formalizes a position maintained across eight years of the author's scholarship: reputation, the standing value of a relationship, is the accountability substrate, and collateral is not. 2026
  32. The evaluations measure what DAOs document about themselves rather than what DAOs do in operation, a source-document constraint the analysis does not claim to overcome. 2026
  33. The two failures interact through the representation choice: a more expressive representation describes more of reality but is harder to reason about, so every governance design must choose where on this frontier to sit. 2026
  34. The appropriate solution concept for a computative economy shifts from competitive equilibrium over a fixed commodity space to recursive equilibrium over an expanding one, positioned as a generalization of the Arrow-Debreu model rather than a re-pricing of it. 2026
  35. Three present-day convergences — capable generative agents, collapsing marginal cost, and existing on-chain coordination substrates with reputation primitives — jointly convert the neoclassical-computative distinction from a forecast into a studiable system. 2026
  36. The propositions separating computative from neoclassical labor markets are concrete hypotheses with neoclassical nulls — on allocation efficiency, participation formation under standing-based entry, cooperation stability under defection incentives, and capture resistance — each evaluable in controlled multi-agent settings now. 2026