Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management
E463929
"Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management" is a management book by Jeffrey Pfeffer that advocates using rigorous evidence and data-driven thinking to make better organizational and leadership decisions.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4726039 — 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: Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management Context triple: [Jeffrey Pfeffer, notableWork, Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management]
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A.
The Cost-Benefit Revolution
The Cost-Benefit Revolution is a book by legal scholar Cass Sunstein that argues for the central role of cost-benefit analysis in modern regulation and public policy.
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B.
Nudge: Improving Decisions About Health, Wealth, and Happiness
"Nudge: Improving Decisions About Health, Wealth, and Happiness" is a popular behavioral economics book by Richard Thaler and Cass Sunstein that explains how subtle changes in choice architecture can steer people toward better decisions without restricting their freedom.
-
C.
"The Nature of the Firm"
"The Nature of the Firm" is a foundational 1937 economic essay by Ronald Coase that explains why firms exist and how transaction costs shape their size and structure.
-
D.
Toulmin model of argumentation
The Toulmin model of argumentation is a framework for analyzing and constructing arguments by breaking them into components such as claim, data, warrant, backing, qualifier, and rebuttal.
-
E.
Evidence-Based Policymaking framework
The Evidence-Based Policymaking framework is a structured approach to designing, implementing, and evaluating public policies using rigorous data analysis, research, and measurable outcomes to inform government decision-making.
- 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: Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management Target entity description: "Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management" is a management book by Jeffrey Pfeffer that advocates using rigorous evidence and data-driven thinking to make better organizational and leadership decisions.
-
A.
The Cost-Benefit Revolution
The Cost-Benefit Revolution is a book by legal scholar Cass Sunstein that argues for the central role of cost-benefit analysis in modern regulation and public policy.
-
B.
Nudge: Improving Decisions About Health, Wealth, and Happiness
"Nudge: Improving Decisions About Health, Wealth, and Happiness" is a popular behavioral economics book by Richard Thaler and Cass Sunstein that explains how subtle changes in choice architecture can steer people toward better decisions without restricting their freedom.
-
C.
"The Nature of the Firm"
"The Nature of the Firm" is a foundational 1937 economic essay by Ronald Coase that explains why firms exist and how transaction costs shape their size and structure.
-
D.
Toulmin model of argumentation
The Toulmin model of argumentation is a framework for analyzing and constructing arguments by breaking them into components such as claim, data, warrant, backing, qualifier, and rebuttal.
-
E.
Evidence-Based Policymaking framework
The Evidence-Based Policymaking framework is a structured approach to designing, implementing, and evaluating public policies using rigorous data analysis, research, and measurable outcomes to inform government decision-making.
- F. None of above. chosen
Statements (37)
| Predicate | Object |
|---|---|
| instanceOf |
book
ⓘ
management book ⓘ |
| advocates |
data-driven decision making
ⓘ
systematic use of empirical evidence ⓘ |
| aimsTo |
help organizations profit from evidence-based practices
ⓘ
improve quality of managerial decisions ⓘ |
| author |
Jeffrey Pfeffer
ⓘ
Robert I. Sutton ⓘ |
| criticizes |
management by intuition alone
ⓘ
reliance on untested management fads ⓘ unquestioned acceptance of business clichés ⓘ |
| emphasizes |
link between evidence-based decisions and performance
ⓘ
use of research findings in organizational practice ⓘ |
| focusesOn |
application of scientific research to management practice
ⓘ
critical evaluation of management fads ⓘ distinguishing facts from half-truths in management ⓘ |
| genre |
business literature
ⓘ
management literature ⓘ non-fiction ⓘ |
| hasPerspective |
skeptical of unverified management practices
ⓘ
supports rigorous testing of management ideas ⓘ |
| intendedAudience |
business leaders
ⓘ
management students ⓘ managers ⓘ |
| language | English ⓘ |
| mainSubject |
decision making in organizations
ⓘ
evidence-based management ⓘ leadership practices ⓘ use of data and evidence in management ⓘ |
| proposes | principles of evidence-based management ⓘ |
| relatedConcept |
leadership effectiveness
ⓘ
organizational behavior ⓘ organizational performance ⓘ |
| relatedWorkOfAuthor |
Jeffrey Pfeffer
ⓘ
Robert I. Sutton ⓘ |
| teaches |
how to avoid common decision-making biases in organizations
ⓘ
how to evaluate the quality of management evidence ⓘ |
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: Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management Description of subject: "Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management" is a management book by Jeffrey Pfeffer that advocates using rigorous evidence and data-driven thinking to make better organizational and leadership decisions.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
Jeffrey Pfeffer
→
notableWork
→
Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management
ⓘ