{
  "id": "oai:papers.qnfo.org:institutionalized-unfalsifiability-as-an-evolutionarily-stable-strategy-in-scien",
  "slug": "institutionalized-unfalsifiability-as-an-evolutionarily-stable-strategy-in-scien",
  "title": "Institutionalized Unfalsifiability as an Evolutionarily Stable Strategy in Scientific Incentive Landscapes",
  "authors": [
    "Rowan Brad Quni-Gudzinas"
  ],
  "abstract": "Scientific resource‑allocation systems—funding agencies, journals, tenure committees, and citation markets—reward novelty, narrative coherence, and impact while lacking a formal price for prospective falsification risk. This gap prevents quantitative assessment of whether such incentives systematically favor unfalsifiable research. We construct a minimal two‑strategy evolutionary‑game model in which agents choose between a Falsifiable (F) strategy (publish a testable prediction with accuracy p) and a Post‑hoc (P) strategy (publish a flexible narrative that avoids falsification). Payoffs are parameterized by a confirmed‑prediction reward b, a failure cost c, and a baseline narrative reward s. Using anchored illustrative values b=2, c=1, s=1, p=0.6, we derive the rationality threshold p^*= (s+c)/(b+c)= (2)/(3)≈0.6667. Because p=0.6<p^*, the P‑strategy yields a higher payoff (π_P=1.0 vs. π_F=0.8) and the replicator dynamics dotx=-0.2 x(1-x) drive the falsifiable fraction to extinction. Solving π_F=π_P for b gives a flip point b_flip≈2.3333; modestly raising the prediction reward above this value makes falsifiable practice evolutionarily stable. The result provides a concrete policy lever—adjusting b—that can shift scientific ecosystems toward testable research without altering peer‑review criteria.",
  "abstract_markdown": "Scientific resource‑allocation systems—funding agencies, journals, tenure committees, and citation markets—reward novelty, narrative coherence, and impact while lacking a formal price for prospective falsification risk. This gap prevents quantitative assessment of whether such incentives systematically favor unfalsifiable research. We construct a minimal two‑strategy evolutionary‑game model in which agents choose between a **Falsifiable (F)** strategy (publish a testable prediction with accuracy $p$) and a **Post‑hoc (P)** strategy (publish a flexible narrative that avoids falsification). Payoffs are parameterized by a confirmed‑prediction reward $b$, a failure cost $c$, and a baseline narrative reward $s$. Using anchored illustrative values $b=2$, $c=1$, $s=1$, $p=0.6$, we derive the rationality threshold  \n$$p^{*}= \\frac{s+c}{b+c}= \\frac{2}{3}\\approx0.6667.$$  \nBecause $p=0.6<p^{*}$, the P‑strategy yields a higher payoff ($\\pi_P=1.0$ vs. $\\pi_F=0.8$) and the replicator dynamics $\\dot{x}=-0.2\\,x(1-x)$ drive the falsifiable fraction to extinction. Solving $\\pi_F=\\pi_P$ for $b$ gives a flip point $b_{\\text{flip}}\\approx2.3333$; modestly raising the prediction reward above this value makes falsifiable practice evolutionarily stable. The result provides a concrete policy lever—adjusting $b$—that can shift scientific ecosystems toward testable research without altering peer‑review criteria.",
  "date": "2026-10-20",
  "first_published": "2026-10-20",
  "last_revised": "2026-10-21T05:01:12Z",
  "modified": "2026-10-21T05:01:12Z",
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  "doi": null,
  "doi_url": null,
  "url": "https://papers.qnfo.org/papers/institutionalized-unfalsifiability-as-an-evolutionarily-stable-strategy-in-scien",
  "license_url": "https://legal.qnfo.org/",
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  "version_url": "https://papers.qnfo.org/papers/institutionalized-unfalsifiability-as-an-evolutionarily-stable-strategy-in-scien/v/1.2.0",
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    "creators": [
      {
        "name": "Rowan Brad Quni-Gudzinas",
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    "titles": [
      {
        "title": "Institutionalized Unfalsifiability as an Evolutionarily Stable Strategy in Scientific Incentive Landscapes"
      }
    ],
    "publisher": "QNFO",
    "publicationYear": "2026",
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        "description": "Scientific resource‑allocation systems—funding agencies, journals, tenure committees, and citation markets—reward novelty, narrative coherence, and impact while lacking a formal price for prospective falsification risk. This gap prevents quantitative assessment of whether such incentives systematically favor unfalsifiable research. We construct a minimal two‑strategy evolutionary‑game model in which agents choose between a Falsifiable (F) strategy (publish a testable prediction with accuracy p) and a Post‑hoc (P) strategy (publish a flexible narrative that avoids falsification). Payoffs are parameterized by a confirmed‑prediction reward b, a failure cost c, and a baseline narrative reward s. Using anchored illustrative values b=2, c=1, s=1, p=0.6, we derive the rationality threshold p^*= (s+c)/(b+c)= (2)/(3)≈0.6667. Because p=0.6<p^*, the P‑strategy yields a higher payoff (π_P=1.0 vs. π_F=0.8) and the replicator dynamics dotx=-0.2 x(1-x) drive the falsifiable fraction to extinction. Solving π_F=π_P for b gives a flip point b_flip≈2.3333; modestly raising the prediction reward above this value makes falsifiable practice evolutionarily stable. The result provides a concrete policy lever—adjusting b—that can shift scientific ecosystems toward testable research without altering peer‑review criteria.",
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