The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index; 1 of the 13 sources its claims cite were checked for support.
Is Semantic Information Meaningful Data?
Open accessAbstract
There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
Floridi argues that the Standard Definition of Information (SDI) as well-formed, meaningful data gives only necessary but insufficient conditions for semantic information, because truth-values do not supervene on information and misinformation is pseudo-information rather than a type of information. He revises SDI into RSDI by adding a fourth, necessary truth-condition, aligning with the Dretske–Grice approach.
Key findings
- SDI is formulated as: σ is DOS (declarative, objective, semantic) information iff (1) σ consists of n data (d), n ≥ 1; (2) the data are well-formed; (3) the well-formed data are meaningful. Floridi holds these are necessary but not sufficient.
- The paper rejects alethic neutrality (AN) — the claim that meaningful, well-formed data qualify as information regardless of truth-value — and with it the consequences that false information (FI) is a genuine type of information, that tautologies qualify as information (TA), and that "it is true that σ" is non-redundant (TI).
- Nine proposed reasons for treating false information as a type of semantic information (FI.1–FI.9) are each argued to be unconvincing; two positive arguments are given that misinformation is pseudo-information: (a) "false" in "false information" is attributive and negative, so the compound fails the splitting test (unlike "digital information"), and (b) if false information counted as information, semantic erosion by operators like "not" would be inexplicable.
- The revised definition (RSDI) adds a fourth condition: the meaningful, well-formed data are truthful. Five areas of application are listed, including critique of deflationary theories of truth, mathematical/analytic propositions, empty names, the standard definition of knowledge, and a quantitative theory of semantic information based on truth-values and degrees of discrepancy rather than probability distributions.
Methods
- Conceptual/philosophical analysis, not empirical: the paper works within situation logic (Israel and Perry; Devlin), using the symbol σ and the term "infon" for discrete items of information irrespective of semiotic code or physical implementation.
- The argument proceeds by (i) formalising SDI and its four endorsed neutralities (typological, taxonomic, ontological, genetic), (ii) rejecting the fifth, alethic neutrality, (iii) rebutting nine reasons for counting false information as information, and (iv) supplying two constructive arguments that it is pseudo-information.
- Illustrative examples are used throughout (e.g. a dinner-guests scenario, a "false constable," the EREP CD-ROM database, Poe's raven as a unary device, hieroglyphics before the Rosetta Stone).
Limitations
- Stated by the paper: the rejection of TA (tautologies as information) is not pursued because it is "crucially connected to the interpretation of mathematical and analytic truths" and is left to another paper; arguments against AN based on deflationary theories of truth and a criticism of TI are also deferred as beyond the paper's scope.
- Stated by the paper: the analysis is deliberately restricted to declarative, objective and semantic (DOS) information; non-declarative uses of "information" (stipulations, invitations, orders, instructions, game moves, music files, digital paintings) and the mathematical/pragmatic senses tied to uncertainty, probability and decision utility are explicitly excluded.
- Evident from the text: the argument is conceptual and illustrative rather than empirical, resting on linguistic intuitions (e.g. the attributive/predicative test, the "false constable" analogy) and on the plausibility of the semantic-erosion argument, with no data or formal proof offered for the central claim.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
44 Own interpretation · 3 Not checked yet · 3 No basis given · 2 Sources not found · 1 Partly supported · accuracy not yet measured
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“None of these consequences seems ultimately defensible”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“SDI is incorrect because truth-values do not supervene on semantic information”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
- The authors state this as an assumption: Objective semantic information is taken to have a declarative or factual value, i.e., it is supposed to be correctly qualifiable alethically.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“their rejection forces a revision of AN and hence of SDI.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“none of the reasons for interpreting misinformation as a type of semantic information is convincing”
- Also stated in: § It follows that · p. 10 · hedged
“none of the main reasons that could be adduced for interpreting false information as a type of information is convincing”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: The reasons considered in the paper are the main reasons for interpreting misinformation as a type of semantic information.
- Also stated in: § It follows that · p. 10 · hedged
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“there are compelling reasons to treat it as pseudo-information”
- Also stated in: § It follows that · p. 10 · boosted
“there are compelling reasons to treat false and tautological information as pseudo-information”
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § It follows that · p. 10 · boosted
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As a consequence, SDI is revised to include a necessary truth-condition.”
- Also stated in: § 1. Introduction · p. 2 · plain
“It follows that SDI needs to be revised by adding a necessary truth-condition.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: The rejection of FI alone is sufficient to force a revision of AN and hence of SDI.
- Also stated in: § 1. Introduction · p. 2 · plain
None of the sources cited for this claim have been checked yet.
In the paper
“The bipartite account has gained sufficient consensus to become an operational standard in fields that tend to deal with data and information as reified entities”
What the sources say
- Not matchedcites Davis and Olson (1985)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Silver and Silver (1989)
- Not matchedcites Checkland and Scholes (1990)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Meaning is not (at least not only) in the mind of the user.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information.”
- Also stated in: § 2.1. An Analysis of the Standard Definition of Information · p. 9 · plain
“insofar as SDI provides necessary conditions for σ to qualify as DOS information, it also endorses four types of neutrality: TN, TaxN, ON and GN.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § 2.1. An Analysis of the Standard Definition of Information · p. 9 · plain
- Probably not a substantial claim. 26
- It may state two separate claims as one. 8
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“There is no consensus yet on the definition of semantic information.”
- Also stated in: § 1. Introduction · p. 1 · plain
“recent surveys have shown no consensus on a single, unified definition of semantic information.¹”
What the sources say
- Partly supportedcites Floridi [2002], [2004a], [2005] sourceExperimental — accuracy not yet measured
Section 5 (p. 137) says there is no consensus on a single, unified definition of information. It mentions a proposed revision to the definition of semantic information, but does not specifically say there is no consensus on that narrower definition. (LLM, conf=0.85)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Also stated in: § 1. Introduction · p. 1 · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“ON) no information without data representation.”
plain- Asserted: fails — The authors may not put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The authors may not put it forward as true.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“According to SDI, alethic values are not embedded in, but supervene on semantic information:”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- The authors state this as an assumption: Objective semantic information is taken to have a declarative or factual value, i.e., it is supposed to be correctly qualifiable alethically.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“TaxN) a datum is a relational entity.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“GN) δ can have a semantics independently of any informee.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The question is whether it is rigorous enough to be applied in the context of an informationtheoretical epistemology. We shall see that this is not the case”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“FI may be coupled to some true, metainformation M that the source of FI is not fully reliable. What now counts as information is the true M, not the false FI.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Over the last three decades, most analyses have supported a definition of DOS information in terms of data + meaning.”
What the sources say
- Not matchedcites Davis and Olson (1985)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Silver and Silver (1989)
- Not matchedcites Checkland and Scholes (1990)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The standard definition of DOS information (SDI) provides necessary but insufficient conditions for the qualification of data as information.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is not the case, and hence it would be a mistake or an act of misinformation to assert, that p constitutes information about the number of natural satellites orbiting around the earth and is also a falsehood.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“misinformation (false information) has turned out to be not a type of information but rather pseudo-information.”
- Also stated in: § 6. The standard definition of information revised · p. 16 · plain
“False information is not an inferior kind of information; it just is not information.”
- Also stated in: § 6. The standard definition of information revised · p. 16 · plain
“[...] false information and mis-information are not kinds of information——any more than decoy ducks and rubber ducks are kinds of ducks.”
What the sources say
- Not matchedcites Dretske (1981), 45
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Grice (1989), 371
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
- Also stated in: § 6. The standard definition of information revised · p. 16 · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is not an oxymoron, but a way of specifying that the contents in question do not conform to the situation they purport to map.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it also endorses four types of neutrality: TN, TaxN, ON and GN.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The confusion about the nature of false information seems to be generated by a misleading analogy.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the attributive use can be either positive or negative.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“S.4 is one of the earliest and most popular formulations of SDI”
What the sources say
- Not matchedcites Bateson (1973)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If false information were a genuine type of information it should pass the splitting test. It does not, so it is not.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“to exchange (receive, sell, buy, etc.) false DOS information about x, e.g. the number of moons orbiting around the earth, is to exchange (receive, sell, buy, etc.) no DOS information at all about x, only meaningful and well-formed data, that is semantic content.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we ordinarily speak of false information when what we mean is misinformation, i.e. no information at all.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“if they are not truthful, they can only constitute misinformation”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“this merely shows that FI is a compound in which only the true component B qualifies as information.”
plain- Asserted: fails — The authors may not put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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Probably not a substantial claim. The authors may not put it forward as true. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“More recently, the bipartite account has begun to influence the philosophy of computing and information as well”
What the sources say
- Not matchedcites Chalmers [1996]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Floridi [1999]
- Not checked — no full text of the sourcecites Franklin [1995]
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In conclusion, there seem to be no good reason to treat false information as a type of information.”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: Ordinary uses of technical words may be too generic and idiosyncratic, if not incorrect, to provide conceptual guidelines.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it follows that SDI needs to be modified, to include a fourth condition about the positive alethic nature of the data in question”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“if the mathematical theorem is not correct (if p is false), it must be concluded that Q is misinformed (i.e. not informed) that p (Q does not have any information about the theorem).”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“SDI.3 only requires the δ to be provided with a semantics already.”
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“a false constable (attributive use) is clearly not a specific type of constable, but not a constable at all (negative use)”
boosted- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“DTT may be satisfactory as theories of truth-ascriptions while being inadequate as theories of truthfulness”
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
The authors state this as an assumption.
Objective semantic information is taken to have a declarative or factual value, i.e., it is supposed to be correctly qualifiable alethically.
“where objective semantic information is taken to have a declarative or factual value, i.e., it is suppose to be correctly qualifiable alethically.”
The paper relies on this without support.
The reasons considered in the paper are the main reasons for interpreting misinformation as a type of semantic information.
“none of the main reasons that could be adduced for interpreting false information as a type of information is convincing”
The authors state this as an assumption.
The rejection of FI alone is sufficient to force a revision of AN and hence of SDI.
“For the sake of simplicity, in the rest of this article only the rejection of FI will be pursued”
The paper relies on this without support.
Sources of information are usually supposed to be truth-oriented or truth-tracking by default.
“sources of information are usually supposed to be truth-oriented or truth-tracking by default”
The paper relies on this without support.
The cloth of semantic information can be, and indeed is, often undone by equally semantic means.
“We know that the cloth of semantic information can be, and indeed is, often undone by equally semantic means.”
The paper relies on this without support.
Ordinary uses of technical words may be too generic and idiosyncratic, if not incorrect, to provide conceptual guidelines.
“ordinary uses of technical words may be too generic and idiosyncratic, if not incorrect, to provide conceptual guidelines.”
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?
The cited source says what the claim attributes to it.
In the citing paper
“The most articulate defense of VTNN has been offered by Floridi (2005, 2007), who gives two main arguments in support of the thesis that false ''nonnatural information'' is not really information: the argument from splitting and the argument from semantic loss .”
From INFORMATION WITHOUT TRUTH (2010) · cites this paper as Floridi 2005
The cited source says what the claim attributes to it.
In the citing paper
“The most articulate defense of VTNN has been offered by Floridi (2005, 2007), who gives two main arguments in support of the thesis that false ''nonnatural information'' is not really information: the argument from splitting and the argument from semantic loss .”
From INFORMATION WITHOUT TRUTH (2010) · cites this paper as Floridi 2005
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ 2. The Standard Definition of Information · p. 3
“Chalmers [1996]”
§ References · p. 19
“Chalmers, D. J. 1997, The Conscious Mind: in Search of a Fundamental Theory (Oxford: Oxford University Press).”
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What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligence
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A defence of informational structural realism
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“In this technical sense, one never deals epistemically with pure data but only with somewhat interpreted data (in semantics, this is often referred to as content , see Floridi (2005b)).”
BackgroundSelf-citationFour challenges for a theory of informational privacy
Floridi, L. (2006) · Ethics and Information Technology · doi:10.1007/s10676-006-9121-3 · Cited by 160
Self-citationInformation About Information: A Taxonomy of Views1
McKinney, & Yoos, C. J. (2010) · MIS Quarterly · doi:10.2307/20721430 · Cited by 158
von der Gracht, H. A., Vennemann, C. R., & Darkow, I. (2009) · Futures · doi:10.1016/j.futures.2009.11.023 · Cited by 157
How many dimensions of biodiversity do we need?
Lyashevska, O., & Farnsworth, K. D. (2012) · Ecological Indicators · doi:10.1016/j.ecolind.2011.12.016 · Cited by 142
Philosophical Conceptions of Information
Floridi, L. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-00659-3_2 · Cited by 125
“…Information Science, in Information Systems Theory, Methodology, Analysis and Design, in Information (Systems) Management, in Database Design and in Decision Theory have adopted a General Definition of Information (GDI) in terms of data + meaning (see Floridi 2005b) for an extended bibliography).”
MethodSelf-citationLiving is Information Processing: From Molecules to Global Systems
Farnsworth, K. D., Nelson, J., & Gershenson, C. (2013) · Acta Biotheoretica · doi:10.1007/s10441-013-9179-3 · Cited by 124
“space/time and matter/energy) which has grown within physics over the past several decades, accompanied by a new philosophical position which places information at the core of determining reality [termed ‘Informational Structural Realism’ by Floridi (2003)].”
BackgroundInfluentialSCARANTINO, A., & PICCININI, G. (2010) · Metaphilosophy · doi:10.1111/j.1467-9973.2010.01632.x · Cited by 119
Torres, R., Gerhart, N., & Negahban, A. (2018) · ACM SIGMIS Database: the DATABASE for Advances in Information Systems · doi:10.1145/3242734.3242740 · Cited by 113
“Important in our selection of this particular view of information is the acknowledgement that information has meaning to the cognitive agent and that this meaning is rooted in truth (Capurro & Hjørland, 2003; Floridi, 2005).”
BackgroundComputation vs. information processing: why their difference matters to cognitive science
Piccinini, G., & Scarantino, A. (2010) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2010.07.012 · Cited by 110
Understanding Epistemic Relevance
Floridi, L. (2007) · Erkenntnis · doi:10.1007/s10670-007-9087-5 · Cited by 102
“Regarding the former, we now have a clear analysis; regarding the latter, elsewhere (Floridi 2005b) I have shown that misinformation is ‘‘well-formed and meaningful data (i.e. semantic content) that is false’’.”
BackgroundSelf-citationA Conceptual Analysis of Disinformation
Fallis, D. (2009) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 101
Algorithmic detection of misinformation and disinformation: Gricean perspectives
Søe, S. O. (2017) · Journal of Documentation · doi:10.1108/jd-05-2017-0075 · Cited by 99
““ Inaccurate information (or misinformation) can mislead people whether it results from an honest mistake, negligence, unconscious bias, or (as in the case of disinformation) intentional deception ” (Fallis, 2014, p. 136).”
BackgroundMethodInfluentialPhilosophy and information studies
Furner, J. (2010) · Annual Review of Information Science and Technology · doi:10.1002/aris.2010.1440440111 · Cited by 82
Impossible Worlds and the Logic of Imagination
Berto, F. (2017) · Erkenntnis · doi:10.1007/s10670-017-9875-5 · Cited by 81
An integrative semiotic framework for information systems: The social, personal and material worlds
Mingers, J., & Willcocks, L. P. (2014) · Information and Organization · doi:10.1016/j.infoandorg.2014.01.002 · Cited by 83
“Similar ideas have been proposed recently by Floridi (2005, 2011).”
BackgroundThe need for ‘skeptical’ accountants in the era of Big Data
McKinney, E. H., Yoos, C. J., & Snead, K. C. (2017) · Journal of Accounting Education · doi:10.1016/j.jaccedu.2016.12.007 · Cited by 87
Information, Ethics, and Computers: The Problem of Autonomous Moral Agents
Stahl, B. C. (2003) · Minds and Machines · doi:10.1023/b:mind.0000005136.61217.93 · Cited by 75
“Floridi, forthcoming ). Critics might point out that this relationship of information and truth is tautological.”
BackgroundA unified account of information, misinformation, and disinformation
Søe, S. O. (2019) · Synthese · doi:10.1007/s11229-019-02444-x · Cited by 97
“As such, information and misinformation are opposites and disinformation is the part of misinformation that is purposefully misleading (Floridi 2005a, b).”
InfluentialThe Informational Turn in Philosophy1
Adams, F. (2003) · Minds and Machines · doi:10.1023/a:1026244616112 · Cited by 74
Semantic information and the network theory of account
Floridi, L. (2010) · Synthese · doi:10.1007/s11229-010-9821-4 · Cited by 72
“3 See for example the discussion in Fetzer (2004), who criticises Floridi (2004c), with a reply in Floridi (2005); or the objections moved by Colburn (2000a), Colburn (2000b) and Dodig-Crnkovic (2005).”
BackgroundSelf-citationA computational interpretation of conceptivism
Ferguson, T. M. (2014) · Journal of Applied Non-Classical Logics · doi:10.1080/11663081.2014.980116 · Cited by 68
“In Floridi (2005, p. 355), Luciano Floridi gave an example that illustrates this distinction well.”
BackgroundExploring Knowledge Entropy in Organizations
Brătianu, C. (2019) · Management Dynamics in the Knowledge Economy · doi:10.25019/mdke/7.3.05 · Cited by 67
“Floridi (2005, 2012, 2013) performs a philosophical analysis of the extensional interpretation of the information and information entropy concepts showing the difficulties and limitations of that extension.”
BackgroundAlgorithmic rationality: Epistemology and efficiency in the data sciences
Lowrie, I. (2017) · Big Data & Society · doi:10.1177/2053951717700925 · Cited by 69
“In so doing, I am somewhat short-circuiting ongoing debates in the second-order sociology and philosophy of science about the definition of data (Leonelli, 2015) and information (Floridi, 2005).”
BackgroundThe Philosophy of Information: Ten Years Later
Floridi, L. (2011) · doi:10.1002/9781444396836.ch10 · Cited by 66
Self-citationField and Airborne Spectroscopy Cross Validation—Some Considerations
Hueni, A., Damm, A., Kneubühler, M., et al. (2016) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2016.2593984 · Cited by 65
Semantic Information and the Correctness Theory of Truth
Floridi, L. (2010) · Erkenntnis · doi:10.1007/s10670-010-9249-8 · Cited by 61
“3 See for example the discussion in Fetzer (2004), with a reply in Floridi (2005); or the objections moved by Colburn (2000a, b) and Dodig-Crnkovic (2005).”
BackgroundSelf-citationDigital hermeneutics: from interpreting with machines to interpretational machines
Romele, A., Severo, M., & Furia, P. (2018) · AI & Society · doi:10.1007/s00146-018-0856-2 · Cited by 69
“In the semantic theory of information developed by Floridi (2005, 2010, 2015) this perspective has been neglected, because semantic information is defined as meaningful (and true) per se.”
BackgroundThe enduring scandal of deduction
D’Agostino, M., & Floridi, L. (2008) · Synthese · doi:10.1007/s11229-008-9409-4 · Cited by 60
“This is what is often meant by saying that tautologies and inferences are “analytical”.2 1 Floridi (2004, 2005), see Bremer and Cohnitz (2004, Chap.”
BackgroundSelf-citationNotes from the underground city of disinformation: A conceptual investigation
Karlova, N., & Lee, J. H. (2011) · Proceedings of the American Society for Information Science and Technology · doi:10.1002/meet.2011.14504801133 · Cited by 64
“Building from Dretske (1983), Floridi (2005, 2010) argued that because false information is not information and because misinformation and disinformation are false, neither misinformation nor disinformation qualifies as information.”
BackgroundAdolwa, I. S., Okoth, P. F., Mulwa, R. M., et al. (2012) · The Journal of Agricultural Education and Extension · doi:10.1080/1389224x.2012.638782 · Cited by 55
Syntactical Informational Structural Realism
Beni, M. D. (2018) · Minds and Machines · doi:10.1007/s11023-018-9463-8 · Cited by 53
“The amount of informativeness of each ri is evaluated as a function of the alethic value possessed by ri (Floridi 2005, 205).”
BackgroundSimple Hyperintensional Belief Revision
Berto, F. (2018) · Erkenntnis · doi:10.1007/s10670-018-9971-1 · Cited by 52
“2 If, as claimed e.g. by Floridi (2005), information is factive, that is, being informed that / entails / , then there cannot be inconsistent information unless, as believed by dialetheists like Priest (1987), there are true contradictions.”
BackgroundOrganised complexity, meaning and understanding
Bawden, D. (2007) · Aslib Journal of Information Management · doi:10.1108/00012530710817546 · Cited by 52
“Floridi (2005), an exponent of a new interest in the “philosophy of information” within the discipline of philosophy itself, recasts the idea of knowledge as “justified, true belief” into the idea that information is “well-formed, meaningful and truthful data”[15].”
BackgroundFrom Knowledge to Wisdom: Looking beyond the Knowledge Hierarchy
Brătianu, C., & Bejinaru, R. (2023) · Knowledge · doi:10.3390/knowledge3020014 · Cited by 50
“He focused on information from a philosophical perspective, trying to extend the work done by other researchers in defining semantic information [26,27].”
BackgroundTurilli, M. (2007) · Ethics and Information Technology · doi:10.1007/s10676-006-9128-9 · Cited by 48
TRENDS IN THE PHILOSOPHY OF INFORMATION
Floridi, L. (2008) · Elsevier eBooks · doi:10.1016/b978-0-444-51726-5.50009-1 · Cited by 48
Self-citationOn Quantifying Semantic Information
D’Alfonso, S. (2011) · Information · doi:10.3390/info2010061 · Cited by 45
“Without getting caught up in the veridicality thesis debate [22,23], in this paper semantic information is defined as true semantic content and semantic misinformation is defined as false semantic content.”
BackgroundInfluentialCyber-Physical Systems of Systems
Bondavalli, A., Bouchenak, S., & Kopetz, H. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-47590-5 · Cited by 44
Santos-d’Amorim, K., & Miranda, M. K. F. D. O. (2021) · Encontros Bibli Revista Eletrônica de Biblioteconomia e Ciência da Informação · doi:10.5007/1518-2924.2021.e76900 · Cited by 62
Social welfare implications of the digital divide
Kim, E., Lee, B., & Menon, N. M. (2009) · Government Information Quarterly · doi:10.1016/j.giq.2008.11.004 · Cited by 42
INFORMATION IN COMPUTER SCIENCE
Dunn, J. M. (2008) · Elsevier eBooks · doi:10.1016/b978-0-444-51726-5.50019-4 · Cited by 39
Consciousness: a unique way of processing information
Marchetti, G. (2018) · Cognitive Processing · doi:10.1007/s10339-018-0855-8 · Cited by 49
“For example, Egyptian hieroglyphics were already regarded as information before the discovery of the Rosetta Stone, even if their semantics was beyond the comprehension of any interpreter (see, Floridi 2005).”
BackgroundThe Metaphilosophy of Information
Sequoiah-Grayson, S. (2007) · Minds and Machines · doi:10.1007/s11023-007-9072-4 · Cited by 40
PUTTING INFORMATION FIRST: LUCIANO FLORIDI AND THE PHILOSOPHY OF INFORMATION
Allo, P. (2010) · Metaphilosophy · doi:10.1111/j.1467-9973.2010.01646.x · Cited by 39
A Critical Analysis of Floridi’s Theory of Semantic Information
Adriaans, P. (2010) · Knowledge, technology & policy/Knowledge in society/Knowledge, technology, & policy · doi:10.1007/s12130-010-9097-5 · Cited by 40
“…survey I did among colleagues a couple of years ago revealed that almost none of them took these distinctions to be very clear or valuable, but from the writings of Floridi we learn that there exist ‘ consensus ’ on a general definition of information (GDI) as: data + meaning (Floridi 2005a, b).”
Kettinger, W. J., Zhang, C., & Chang, K. (2013) · Information Systems Research · doi:10.1287/isre.1120.0473 · Cited by 45
Spence, E. H. (2011) · Ethics and Information Technology · doi:10.1007/s10676-011-9265-7 · Cited by 38
Using FLOW to Improve Communication of Requirements in Globally Distributed Software Projects
Stapel, K., Knauss, E., & Schneider, K. A. (2009) · doi:10.1109/circus.2009.6 · Cited by 37
“Information is data plus meaning [16].”
Perception and Testimony as Data Providers
Floridi, L. (2013) · Studies in history and philosophy of science · doi:10.1007/978-94-007-6973-1_4 · Cited by 36
“This will build upon the naturalistic, action-based semantics developed in (Floridi 2011; Taddeo and Floridi 2005, 2007), and provide the missing link between that kind of semantics and the richer, more convention-based semantics enjoyed by Alice and Bob when having an ordinary conversation,…”
BackgroundMethodSelf-citationAlbrecht, J. (2020) · Geographic Information Science & Technology Body of Knowledge · doi:10.22224/gistbok/2020.2.1 · Cited by 35
Simion, M. (2023) · Episteme · doi:10.1017/epi.2023.25 · Cited by 35
“The American Library Association (2005) has issued a ‘ Resolution on Disinformation, Media Manipulation, and the Destruction of Public Information.”
BackgroundDo we have moral duties towards information objects?
Brey, P. A. E. (2008) · Ethics and Information Technology · doi:10.1007/s10676-008-9170-x · Cited by 35
“In his own philosophical theory of information, for example, Floridi distinguishes between two kinds of information, semantic and environmental, both of which he describes as receiverrelative (Floridi 2005a, b).”
BackgroundThe logic of ‘being informed’ revisited and revised
Allo, P. (2010) · Philosophical Studies · doi:10.1007/s11098-010-9516-1 · Cited by 33
An Illustrated Introduction to the Infosphere
Martens, B. V. D. V. (2015) · Library trends · doi:10.1353/lib.2015.0006 · Cited by 33
“Levels of Abstraction and Gradients of Abstraction The LoA method is adapted from formalized modeling often used in information system design (Greco, Paronitti, Turilli, & Floridi, 2005), which in itself draws from metaphysics, particularly ontological design (Artz, 1997).”
BackgroundMethodInfluentialWhat is Information? A multidimensional concern
Nafría, J. M. D. (2010) · tripleC Communication Capitalism & Critique Open Access Journal for a Global Sustainable Information Society · doi:10.31269/triplec.v8i1.76 · Cited by 34
“…information – such as in Weaver (Shannon & Weaver 1949) – while others consider a weak restriction allowing a large margin of freedom (Sloman 1978, Floridi 2005c, §4).18 In Figure 2 (not trying to be exhaustive once again), it is shown the extent to which each concept answers to the posed…”
BackgroundMethodInfluentialBig Data, digital demand and decision-making
Green, S., McKinney, E. H., Heppard, K. A., & Garcia, L. (2018) · International Journal of Accounting and Information Management · doi:10.1108/ijaim-02-2017-0019 · Cited by 31
Saab, D. J., & Riss, U. V. (2011) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21615 · Cited by 30
“It regards information as a process that changes the subject’s”
BackgroundInfluentialFloridi’s “Open Problems in Philosophy of Information”, Ten Years Later
Dodig-Crnković, G., & Hofkirchner, W. (2011) · Information · doi:10.3390/info2020327 · Cited by 35
A semantic-based framework for automated rule checking in healthcare construction projects
Soliman-Junior, J., Formoso, C. T., & Tzortzopoulos, P. (2019) · Canadian Journal of Civil Engineering · doi:10.1139/cjce-2018-0460 · Cited by 30
The Paradox of Inference and the Non-Triviality of Analytic Information
Duží, M. (2010) · Journal of Philosophical Logic · doi:10.1007/s10992-010-9127-5 · Cited by 32
“My starting-point is the characterisation of information as being objective and semantic, as found in Floridi (2004, 2005).”
BackgroundMethodBiology transcends the limits of computation
Marshall, P. (2021) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2021.04.006 · Cited by 30
Problems with theories that equate consciousness with information or information processing
Pockett, S. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00225 · Cited by 27
“In information philosophy, Floridi (2005) says “ ‘information’ is often used to refer to non-mental, user-independent, declarative semantic contents, embedded in physical implementations like databases, encyclopedias, web sites, television programmes and so on. . . the Cambridge Dictionary of…”
BackgroundA Conceptual Model for the Information Transfer in Systems-of-Systems
Kopetz, H. (2014) · IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing (ISORC) · doi:10.1109/isorc.2014.19 · Cited by 26
Functional complexity: The source of value in biodiversity
Farnsworth, K. D., Lyashevska, O., & Fung, T. (2012) · Ecological Complexity · doi:10.1016/j.ecocom.2012.02.001 · Cited by 26
“This definition coincides with the ‘diaphoric definition of data’ (Floridi, 2003, 2005), in which a binary (Boolean) bit is the unit of data and a bit is a single difference in any system.”
MethodBasic Concepts on Systems of Systems
Ceccarelli, A., Bondavalli, A., Frömel, B., Höftberger, O., & Kopetz, H. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-47590-5_1 · Cited by 27
An epistemic logic for becoming informed
Primiero, G. (2008) · Synthese · doi:10.1007/s11229-008-9413-8 · Cited by 25
“This basic definition has been extended in Floridi (2004, 2005), where Semantic Information is defined as meaningful, well-formed and veridical data (TSSI).”
BackgroundInfusing Ethical Considerations in Knowledge Management Scholarship: Toward a Research Agenda
Chatterjee, S., & Sarker, S. (2013) · Journal of the Association for Information Systems · doi:10.17705/1jais.00339 · Cited by 28
The SPECCHIO Spectral Information System
Hueni, A., Chisholm, L., Ong, C. C. H., et al. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3025117 · Cited by 24
THE PHILOSOPHY OF INFORMATION: TEN YEARS LATER
Floridi, L. (2010) · Metaphilosophy · doi:10.1111/j.1467-9973.2010.01647.x · Cited by 23
Self-citationWhat Is Nature-Like Computation? A Behavioural Approach and a Notion of Programmability
Zenil, H. (2013) · Philosophy & Technology · doi:10.1007/s13347-012-0095-2 · Cited by 24
System Modeling and Information Semantics
Dodig-Crnković, G. (2005) · Chalmers Research (Chalmers University of Technology) · Cited by 23
Floridi, L. (2004) · doi:10.1002/9780470757017.ch4 · Cited by 23
Self-citationProtecting infrastructure performance from disinformation attacks
Jamalzadeh, S., Barker, K., González, A. D., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-16832-w · Cited by 21
“Among all critical infrastructures, the electric power grid has been attractive to scholars for several reasons: (1) the electric power grid has been at great risk of attack and threats tremendously74; (2) electric power grid has been relatively more expensive than other infrastructures75; (3) the electric grid is one…”
BackgroundInformation Ethics as a Guide for New Media
Spence, E. H., & Quinn, A. (2008) · Journal of Mass Media Ethics · doi:10.1080/08900520802490889 · Cited by 21
Dinneen, J. D., & Brauner, C. (2015) · Library trends · doi:10.1353/lib.2015.0012 · Cited by 23
“In retort to arguments like these, Floridi (2005) has provided reasons why various resistances to the veridicality thesis are flawed.”
BackgroundKnowledge transfer: an information theory perspective
Sudhindra, S., Ganesh, L. S., & Kaur, A. (2017) · Knowledge Management Research & Practice · doi:10.1057/s41275-017-0060-z · Cited by 21
“More specifically, information theory has been used to explore the constructs of knowledge, information, data and their relationships (Birch 2014; Dretske 1981, 2008; Floridi 2005).”
BackgroundMethodLOGICAL PLURALISM AND SEMANTIC INFORMATION
Allo, P. (2007) · Journal of Philosophical Logic · doi:10.1007/s10992-007-9054-2 · Cited by 21
“9 It is nevertheless important to distinguish the user-independence posited by Floridi (2005) (also referred to as the genetic neutrality of semantic information) from Dretske’s more radical (language independent) realism, according to which a user-independent meaning is to be situated at the level…”
BackgroundInfluentialThe Logic of Fast and Slow Thinking
Solaki, A., Berto, F., & Smets, S. (2019) · Erkenntnis · doi:10.1007/s10670-019-00128-z · Cited by 23
“…a communicative action whereby the source is mostly, but not entirely, trusted; the updated model triggered by [ ⇑] is one where the -satisfying worlds are prioritized in terms of plausibility over the 4 If, as Floridi (2005) claims, information is factive, then there cannot be false information.”
BackgroundInformation Ethics and the Library Profession
Mathiesen, K., & Fallis, D. (2008) · doi:10.1002/9780470281819.ch9 · Cited by 20
Kerr, E. T., & Pritchard, D. (2012) · Philosophy of engineering and technology · doi:10.1007/978-94-007-4292-5_10 · Cited by 19
Prefiguring Floridi’s Theory of Semantic Information
Mingers, J. (2013) · tripleC Communication Capitalism & Critique Open Access Journal for a Global Sustainable Information Society · doi:10.31269/triplec.v11i2.436 · Cited by 19
“The principal argument is very simple – proper quantification (of the sort implied by Floridi’s (2009b) Figure 5 ) requires that the constructs to be quantified can be measured on an interval scale of measurement but much semantic content, especially of a linguistic kind, can only be measured on nominal or ordinal sca…”
BackgroundMethodInfluentialA universal model for the normative evaluation of internet information
Spence, E. H. (2009) · Ethics and Information Technology · doi:10.1007/s10676-009-9204-z · Cited by 19
“For information without truth is not strictly speaking information but either misinformation (the unintentional dissemination of well-formed and meaningful 2 Floridi (2005a).”
BackgroundInfluentialA Unified Approach to Semantic Information and Communication Based on Probabilistic Logic
Choi, J., Loke, S. W., & Park, J. (2022) · IEEE Access · doi:10.1109/access.2022.3228563 · Cited by 21
“One focuses on measuring semantic similarity [8], [9], which often encourages a new way to define meaningful information.”
BackgroundInformation and knowledge à la Floridi
Adams, F. (2011) · doi:10.1002/9781444396836.ch6 · Cited by 19
Epistemology of Construction Informatics
El-Diraby, T. E. (2011) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0000392 · Cited by 18
Nutrigenomic regulation of sensory plasticity
Sung, H., Vaziri, A., Wilinski, D., Woerner, R. K. R., Freddolino, P. L., & Dus, M. (2023) · eLife · doi:10.7554/elife.83979 · Cited by 18
Information, meaning and animal communication
Adams, F., & Beighley, S. M. (2013) · Cambridge University Press eBooks · doi:10.1017/cbo9781139003551.024 · Cited by 18
Khan, S. A., Ojiako, U., Marshall, A. J., et al. (2022) · Engineering Management Journal · doi:10.1080/10429247.2022.2041963 · Cited by 17
The Value of Information: Normativity, Epistemology, and LIS in Luciano Floridi
Fyffe, R. C. (2015) · portal Libraries and the Academy · doi:10.1353/pla.2015.0020 · Cited by 17
How an information perspective helps overcome the challenge of biology to physics
Farnsworth, K. D. (2022) · Biosystems · doi:10.1016/j.biosystems.2022.104683 · Cited by 16
Informational Semantics as a Third Alternative?
Allo, P., & MARES, E. D. (2011) · Erkenntnis · doi:10.1007/s10670-011-9356-1 · Cited by 14
The Philosophical Problem of Truth in Librarianship
Labaree, R. V., & Scimeca, R. (2007) · The Library Quarterly · doi:10.1086/523909 · Cited by 16
Semantic Information and the Trivialization of Logic: Floridi on the Scandal of Deduction
D’Agostino, M. (2013) · Information · doi:10.3390/info4010033 · Cited by 16
Automated interpretation of key performance indicator values and its application in education
Tomić, B., & Milić, T. (2012) · Knowledge-Based Systems · doi:10.1016/j.knosys.2012.08.006 · Cited by 15
“It is generally accepted that data becomes information when meaning is added to it [7,13]:”
Background
Metadata
- Authors
- FLORIDI, L.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- FLORIDI, LUCIANO
- ORCID
- FLORIDI, LUCIANO
- Venue
- Philosophy and Phenomenological Research
- Publisher
- Wiley
- Published
- 2005-03
- Volume
- 70
- Issue
- 2
- Pages
- 351-370
- ISSN
- 0031-8205 (ISSN-L)
- 1933-1592
- OpenAlex
- W2059974307
- Semantic Scholar
- 2af4a76b5eac94619fac8f2a44d008de8f94d58a
- Cited by
- 375
- References
- 40
- Citations by year
- 2026: 10 · 2025: 17 · 2024: 14 · 2023: 21 · 2022: 17 · 2021: 15 · 2020: 11 · 2019: 30 · 2018: 18 · 2017: 19 · 2016: 23 · 2015: 27 · 2014: 20 · 2013: 20 · 2012: 17
- FWCI
- 97.33
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Philosophy and Phenomenological Research (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- University of Hertfordshire Research Archive (University of Hertfordshire) (submittedVersion)
- PhilPapers (PhilPapers Foundation) (submittedVersion)
- Topics
- Social Sciences › Arts and Humanities › Philosophy › Epistemology, Ethics, and Metaphysics
- Social Sciences › Arts and Humanities › Philosophy › Philosophy and Theoretical Science
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Scientific Research and Philosophical Inquiry
- Keywords
- semantic information, misinformation, truth conditions, definition of information
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.
A language model drew the claims from the paper on 2026-10-28, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
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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