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Record W4240457739 · doi:10.4324/9781849772440

Risk Governance

2014· book· en· W4240457739 on OpenAlexaboutno aff
Ortwin Renn

Bibliographic record

Venuenot available
Typebook
Languageen
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessPolitical science

Abstract

fetched live from OpenAlex

�Risk Governance is a tour de force. Every risk manager, every risk analyst, every risk researcher must read this book - it is the demarcation point for all further advances in risk policy and risk research. Renn provides authoritative guidance on how to manage risks based on a definitive synthesis of the research literature. The skill with which he builds practical recommendations from solid science is unprecedented.� Thomas Dietz, Director, Environmental Science and Policy Program, Michigan State University, USA �A masterpiece of new knowledge and wisdom with illustrative examples of tested applications to realworld cases. The book is recommendable also to interested students in different disciplines as a timely textbook on 'risk beyond risk'.� Norio Okada, Full Professor and Director at the Disaster Prevention Research Institute (DPRI), Kyoto University, Japan �There are classic environmental works such as The Tragedy of the Commons by Hardin, Risk Society by Beck, The Theory of Communicative Action by Habermas, and the seminal volumes by Ostrom on governing the commons. Renn�s book fits right into this series of important milestones of environmental studies.� Jochen Jaeger, Professor at Concordia University, Montreal, Canada �Risk Governance provides a valuable survey of the whole field of risk and demonstrates how scientific, economic, political and civil society actors can participate in inclusive risk governance.� Jobst Conrad, Senior Scientist, Social Science Research Center Berlin, Germany �Renn offers a remarkably fair-minded and systematic approach to bringing together the diverse fields that have something to say about 'risk'. Risk Governance moves us along the path from the noisy, formative stage of thinking about risk to one with a stronger empirical, theoretical, and analytical foundation.� Baruch Fischhoff, PhD, Howard Heinz University Professor, Carnegie Mellon University, Pittsburgh, USA 'I cannot describe how impressed I am at the breadth and coherence of Renn's career's work! Written with remarkable clarity and minimal technical jargon... [this] should be required reading in risk courses!' John Graham, former director of the Harvard Risk Center and former deputy director of the Office of Budget and Management of the Unites States Administration This book, for the first time, brings together and updates the groundbreaking work of renowned risk theorist and researcher Ortwin Renn, integrating the major disciplinary concepts of risk in the social, engineering and natural sciences. The book opens with the context of risk handling before flowing through the core topics of assessment, evaluation, perception, management and communication, culminating in a look at the transition from risk management to risk governance and a glimpse at a new understanding of risk in (post)modern societies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.154
Threshold uncertainty score0.514

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0140.009
Open science0.0020.008
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.1540.058

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.181
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations109
Published2014
Admission routes1
Has abstractyes

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Same topicRisk Management in Financial FirmsFrench-language works237,207