Observational selection effects and probability
E173432
"Observational selection effects and probability" is Nick Bostrom’s doctoral thesis, in which he develops a formal framework for understanding how observation bias and self-locating beliefs affect probabilistic reasoning in philosophy and science.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Observational selection effects and probability canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1528602 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Observational selection effects and probability Context triple: [Nick Bostrom, doctoralThesis, Observational selection effects and probability]
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A.
Tolman surface brightness test
The Tolman surface brightness test is an observational cosmology method that checks whether the universe is expanding by examining how the surface brightness of distant galaxies diminishes with redshift.
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B.
Logical Foundations of Probability
Logical Foundations of Probability is a seminal philosophical work by Rudolf Carnap that develops a rigorous logical and formal account of probability and inductive reasoning.
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C.
Advanced Camera for Surveys
The Advanced Camera for Surveys is a high-resolution imaging instrument on the Hubble Space Telescope designed to capture detailed observations of distant galaxies, galaxy clusters, and other faint astronomical objects.
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D.
Drake equation
The Drake equation is a probabilistic formula used to estimate the number of technologically advanced extraterrestrial civilizations that might exist in our galaxy.
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E.
Principles of Stellar Dynamics
Principles of Stellar Dynamics is a foundational astrophysics monograph by Subrahmanyan Chandrasekhar that rigorously develops the theoretical framework for understanding the gravitational dynamics and evolution of stellar systems such as star clusters and galaxies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Observational selection effects and probability Target entity description: "Observational selection effects and probability" is Nick Bostrom’s doctoral thesis, in which he develops a formal framework for understanding how observation bias and self-locating beliefs affect probabilistic reasoning in philosophy and science.
-
A.
Tolman surface brightness test
The Tolman surface brightness test is an observational cosmology method that checks whether the universe is expanding by examining how the surface brightness of distant galaxies diminishes with redshift.
-
B.
Logical Foundations of Probability
Logical Foundations of Probability is a seminal philosophical work by Rudolf Carnap that develops a rigorous logical and formal account of probability and inductive reasoning.
-
C.
Advanced Camera for Surveys
The Advanced Camera for Surveys is a high-resolution imaging instrument on the Hubble Space Telescope designed to capture detailed observations of distant galaxies, galaxy clusters, and other faint astronomical objects.
-
D.
Drake equation
The Drake equation is a probabilistic formula used to estimate the number of technologically advanced extraterrestrial civilizations that might exist in our galaxy.
-
E.
Principles of Stellar Dynamics
Principles of Stellar Dynamics is a foundational astrophysics monograph by Subrahmanyan Chandrasekhar that rigorously develops the theoretical framework for understanding the gravitational dynamics and evolution of stellar systems such as star clusters and galaxies.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf | doctoral thesis ⓘ |
| academicAdvisor | John Leslie ⓘ |
| aim |
to analyze how self-locating beliefs affect probabilities
ⓘ
to clarify the role of observer bias in scientific inference ⓘ to develop a formal framework for observation selection effects ⓘ |
| author | Nick Bostrom ⓘ |
| completionYear | 1997 ⓘ |
| contributorTo |
debate on the Doomsday argument
ⓘ
debate on the Sleeping Beauty problem ⓘ development of anthropic reasoning in analytic philosophy ⓘ formal analysis of observation selection effects ⓘ framework for handling indexical information in probability ⓘ |
| countryOfInstitution | United Kingdom ⓘ |
| degree | PhD in philosophy ⓘ |
| field |
epistemology
ⓘ
philosophy ⓘ philosophy of science ⓘ probability theory ⓘ |
| hasTheoreticalApproach |
Bayesian framework
ⓘ
anthropic reasoning framework ⓘ formal epistemology ⓘ |
| institution |
London School of Economics and Political Science
ⓘ
linked to:
London School of Economics
|
| language | English ⓘ |
| mainSubject |
Bayesian confirmation theory
ⓘ
linked to:
Carnap's continuum of inductive methods
Bayesian epistemology ⓘ Doomsday argument ⓘ Sleeping Beauty problem ⓘ anthropic bias in evidence ⓘ anthropic principles ⓘ anthropic reasoning ⓘ confirmation theory ⓘ fine-tuning of the universe ⓘ indexical information ⓘ methodology of science ⓘ observation bias ⓘ observation selection effects ⓘ observer selection theory ⓘ observer-relative probabilities ⓘ philosophy of cosmology ⓘ probabilistic reasoning ⓘ rational belief updating ⓘ reference class problem ⓘ selection bias ⓘ self-indication assumption ⓘ self-locating beliefs ⓘ self-sampling assumption ⓘ |
| relatedWork | Anthropic Bias: Observation Selection Effects in Science and Philosophy ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Observational selection effects and probability Description of subject: "Observational selection effects and probability" is Nick Bostrom’s doctoral thesis, in which he develops a formal framework for understanding how observation bias and self-locating beliefs affect probabilistic reasoning in philosophy and science.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.