The DOI matches its Crossref record.
Conjectures and Refutations: The Growth of Scientific Knowledge
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Without this clarity, the hypothesis risks becoming what philosopher Karl Popper would call a “metaphysical research program” (Popper 2014)—influential but ultimately unfalsifiable.”
From The myth of the Bayesian brain (2025) · cites this paper as Popper 2014
Citations
Cited by
Sorted by citations
Items 301–326 of 326
Interdisciplinary risks – a delicate balance between trust and critical review
Sahlin, U., & Thorén, H. (2025) · Journal of Risk Research · doi:10.1080/13669877.2025.2526473
“…consider disciplines to be, as e.g. karl Popper does, as merely the label on the door to various university departments that are “distinguished partly for historical reasons and reasons of administrative convenience” (Popper 2014[1963], 88) but that otherwise have little epistemic significance.”
The Foundations of Xorium TheoryPreprint
Hocine, A., & Lozza, S. O. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5378321
Huang, L. (2025) · Review of General Psychology · doi:10.1177/10892680251380430
“As Popper (2014) observed, “ Our knowledge can only be fi nite, while our ignorance must necessarily be in fi nite.”
Conspiracy Theories Are Not Theories: Time To Rename Conspiracy Theories
Reuter, K., & Baumgartner, L. (2025) · Synthese Library/Synthese library · doi:10.1007/978-3-031-98535-5_7
Culturally Responsive Argumentation for Democratic Resilience
Schwed, M. (2025) · Argumentation · doi:10.1007/s10503-025-09684-x
Kontextualisierte Marketinglehre mit KI
Alexander, E. (2026) · Springer eBooks · doi:10.1007/978-3-658-46709-8_70-1
Rationality in Scientific Inquiry: A Retrospective View
Bogale, B. (2026) · Philosophy of Management · doi:10.1007/s40926-025-00358-y
Tijus, C., & Richard, J.-F. (2026) · Enfance · doi:10.3917/enf2.254.0535
Are hopeful narratives more convincing? A laboratory experimentPreprint
Corazzini, L., Diamante, M., & Maggian, V. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6264558
Some Idle and Random Thoughts on Phenomenology and Mental Health
Chung, F. A. J. A. B. M. C. (1996) · Existential Analysis Journal of the Society for Existential Analysis · doi:10.65828/bdgrc507
The words of robotics : a rhetorical approach
Pieters, C. (2020) · doi:10.70675/8470560fzb65ez4704z912fzaf7bdb58a0c3 · Cited by 1
Neurone abstrait : une formalisation de l’intégration dendritique et ses propriétés algébriques
Guinaudeau, O. (2019) · theses.fr (ABES) · doi:10.70675/ba995c77z2c66z4e42zba29zc7005998dee7
The compass of violence : prosperity, decline and the ideological orientation of radical movements
Varaine, S. (2020) · theses.fr (ABES) · doi:10.70675/8ceb37b7z9258z4bd0zaad8z7f4d647d69d7
Smugglers of reference: Expressivist-inferentialism and the inevitability of model denotation
Sartori, L. (2026) · The British Journal for the Philosophy of Science · doi:10.1086/742351
Falsifying Discriminant Validity of Predictive Algorithms
Coston, A. (2026) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3805689.3812310
Grieves, M. W. (2026) · Machines · doi:10.3390/machines14070763
Membrane Models and the Pursuit of Coherence
Kervin, T. A., Zhang, Z., Clark, M., Overduin, M., & Zhang, P. (2026) · Biochemistry · doi:10.1021/acs.biochem.6c00367
From Predictions to Understanding: Explainable Machine Learning in Pharmaceutical CMC Development
Adebar, N., & Smiatek, J. (2026) · doi:10.1021/bk-2026-1529.ch008
Del conexionismo al deep learning. Discusiones para la validación de teorías cognitivas
Goenaga, J., & Castillo, L. (2026) · RHS-Revista Humanismo y Sociedad · doi:10.22209/rhs.v14n2a03
Conceptual challenges in psychiatric nosology: ADHD across six editions of the DSM
Ophir, Y. (2026) · The British Journal of Psychiatry · doi:10.1192/bjp.2026.10768
Evaluating AI feedback: teacher expertise and hidden labour in writing instruction
Li, W., Sulaiman, N. A., & Matore, M. E. E. M. (2026) · English in Education · doi:10.1080/04250494.2026.2723772
Metadata
- Authors
- Popper, K.
- Corresponding author
- Popper, Karl
- Venue
- Routledge eBooks
- Publisher
- Routledge
- Published
- 2014-05-01
- Volume
- 19
- Issue
- 2
- OpenAlex
- W3126953938
- Cited by
- 327
- References
- 0
- Citations by year
- 2026: 22 · 2025: 27 · 2024: 18 · 2023: 27 · 2022: 17 · 2021: 23 · 2020: 14 · 2019: 22 · 2018: 16 · 2017: 9 · 2016: 10 · 2015: 6 · 2014: 7
- FWCI
- 14.52
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- The British Journal for the Philosophy of Science
- Topics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Logic and Philosophy of Science
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
- Social Sciences › Arts and Humanities › History and Philosophy of Science › History and Theory of Mathematics
- Keywords
- conjecture, refutation, scientific reasoning, hypothesis testing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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