Institutionalized Predictive Jeopardy: An Evolutionary-Game Demarcation Criterion for Knowledge Systems

In the paper's words

Institutional knowledge systems — peer review, tenure committees, funding panels, citation markets — must decide which claims deserve resources, yet they possess no formal criterion distinguishing claims that carry prospective falsification risk from claims fitted to evidence after the fact. Incentive structures that cannot price predictive risk plausibly reward post-hoc certainty, allowing unfalsifiable narrative strategies to accumulate. We formalize demarcation as an evolutionary game in which agents choose between a falsifiable strategy F, which submits prospective predictions that can fail publicly, and a post-hoc strategy P, which accommodates any outcome.

The abstract, verbatim, and its opening sentence is the claim. Every line below is quoted from the text.

Numbers it reports

1. The advantage of $F$ is now $$\Delta = 5.6 - 1.0 = 4.6 \gt 0,$$ and the threshold collapses to $$p^{*} = \frac{1+1}{10+1} = \frac{2}{11} \approx 0.1818.$$ An agent needs only 18.18% accuracy for falsifiable practice to be rational — a bar that any functioning forecasting practice clears.

   from 4.4 Intervention: pre-registration and attribution

2. Then $$\pi_F = 0.6\times 2 - (1-0.6)\times 1 = 1.2 - 0.4 = 0.8,$$ while $$\pi_P = s = 1.0.$$ Since $0.8 \lt 1.0$, even a forecaster who is right 60% of the time strictly prefers post-hoc fitting under the baseline configuration.

   from 4.3 Baseline calibration: post-hoc dominance

3. A third is the distributional one: a pay-to-register or infrastructure-mediated system taxes speakers facing 4–6× tokenization premiums [8], converting an epistemic mechanism into an exclusionary one.

   from 7.6 Risks and misuse paths

4. Under a baseline calibration in which publication credit does not distinguish registration from retrofit ($b = 2$, $c = 1$, $s = 1$), a forecaster who is right 60% of the time rationally fits after the fact ($\pi_F = 0.8$ versus $\pi_P = 1.0$), and the system drifts toward unfalsifiable narratives — the formal counterpart of the Head Over Hands pattern [9] and of the Lakatosian observation that axiom-violating theories are expelled rather than adjudicated [10].

   from 8. Conclusion

5. Under a baseline calibration ($b=2$, $c=1$, $s=1$, $p=0.6$), $F$ yields an expected payoff of $0.8$ against $1.0$ for $P$, so post-hoc fitting dominates and the threshold is $p^{*}=2/3\approx 0.6667$.

   from Abstract

6. The contributions are: A two-strategy evolutionary game formalizing institutionalized predictive jeopardy, with the invasion condition for falsifiable practice and the closed-form accuracy threshold $p^{*}=(s+c)/(b+c)$, derived in Sections 4.1–4.2.

   from 1. Introduction

How it is done

1. We derive the closed-form accuracy threshold $p^{*}=(s+c)/(b+c)$ above which falsifiable practice is individually rational.

   from Abstract

2. We derive equilibria, intervention effects, an antifragility condition, and a reform timescale, all with explicit arithmetic.

   from 1. Introduction

3. The QNFO analysis of superdeterminism's reception states the Lakatosian framework explicitly: science operates through research programmes, each defined by a hard core of foundational axioms rendered unfalsifiable by methodological fiat and protected by a belt of auxiliary hypotheses; the structure has a clear procedure for rejecting theories that attack the hard core but no formal path for their comparative assessment or potential acceptance, so such theories are designated unscientific and expelled rather than adjudicated [10].

   from 2. Background and Related Work

4. We model a knowledge-producing community as a population of agents who repeatedly choose one of two strategies when producing a claim: Strategy $F$ (falsifiable practice): the agent registers a prospective prediction before the outcome is known.

   from 3.1 Model overview

What would falsify it

1. Institutional knowledge systems — peer review, tenure committees, funding panels, citation markets — must decide which claims deserve resources, yet they possess no formal criterion distinguishing claims that carry prospective falsification risk from claims fitted to evidence after the fact.

   from Abstract

2. We formalize demarcation as an evolutionary game in which agents choose between a falsifiable strategy $F$, which submits prospective predictions that can fail publicly, and a post-hoc strategy $P$, which accommodates any outcome.

   from Abstract

3. We derive the closed-form accuracy threshold $p^{*}=(s+c)/(b+c)$ above which falsifiable practice is individually rational.

   from Abstract

Where the claim stops

1. The values $b=2$ and $b=10$ are assumptions chosen to represent, respectively, configurations where publication credit does not distinguish registration from retrofit, and configurations with registries and mandatory independent verification [11].

   from 6. Discussion

2. No source supplies measured institutional payoffs; every headline number inherits this assumption.

   from 6. Discussion

3. The linear reliability gain $k/N$ assumes failed claims are removed at no cost and no replacement.

   from 6. Discussion

Where to read

1. Abstract204 words · 1 min
2. 1. Introduction638 words · 3 min
3. 2. Background and Related Work1,325 words · 6 min
4. 3. Methods419 words · 2 min
5. 4. Analysis1,082 words · 5 min
6. 5. Results202 words · 1 min
7. 6. Discussion389 words · 2 min
8. 7. Practical Implications and Engineering Pathways1,379 words · 6 min
9. 8. Conclusion355 words · 2 min
10. Provenance and AI Involvement225 words · 1 min