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Sex Estimation of the Human Skeleton

History, Methods, and Emerging Techniques

Part 1 Introduction to sex estimation 1. A history of sex estimation of human skeletal remains 2. Practitioner preferences for sex estimation from human skeletal remains 3. Applications of sex estimation in paleoanthropology, bioarchaeology, and forensic anthropology 4. The confusion between biological sex and gender and potential implications of misinterpretations 5. Effect of sex misclassification on the skeletal biological profile Part 2 Methods for sex estimation Section A Morphological 6. Pelvis morphology 7. Adult sex estimation from cranial morphoscopic traits 8. Analyses of the postcranial skeleton for sex estimation 9. Parturition markers and skeletal sex estimation &nbsp;Section B Metric 10. Dentition in the estimation of sex 11. Metric methods for estimating sex utilizing the pelvis 12. Sexual dimorphism variation in Fordisc samples Section C Statistics &amp; databases 13. Statistical and machine learning approaches to sex estimation 14. Subadult sex estimation 15. DSP: A probabilistic approach to sex estimation free from population specificity using os coxae measurements 16. MorphoPASSE: Morphological pelvis and skull sex estimation program Part 3 Current considerations/topics 17. Factors of population variation in sex estimation methodology 18. Secular change 19. The effects of skeletal asymmetry on accurate sex classification 20. Cognitive bias in sex estimation: The influence of context on forensic decision-making 21. Sex determination using DNA and its impact on biological anthropology 22. The application of medical imaging to the anthropological estimation of sex

Studies in Penal Theory and Ethics

This book examines whether the two dominant paradigms of punishment theory - retributivism and consequentialism - can be reconciled within a single coherent rationale. It addresses a central problem in criminal law theory and moral philosophy: how punishment can be justified in a way that is both principled and responsive to social consequences. Through a comparative and analytical approach, the book brings together major attempts to bridge the divide between deontological and consequentialist accounts of punishment. It moves from Kant and Bentham to Hegel's project of unification, and then to contemporary theorists including Rawls, Roxin, Brooks, Pawlik, Jakobs, Duff, Tadros, and Zaibert. In doing so, it analyses hybrid, limited, and supra-conceptual approaches across Anglo-American and Continental traditions. The book shows that the classical opposition between retribution and prevention no longer captures the complexity of contemporary punishment theory. Instead, it argues that many competing accounts converge on the idea of punishment as a mechanism of social ordering, while also showing that order cannot be understood merely as something to be maintained or restored. It proposes that any genuinely unifying theory must reconceptualise order as dynamic, contextual, and permeable, while also acknowledging the limits of theoretical unification. The book provides a clear framework for a fragmented debate and offers new perspectives on punishment, legitimacy, and ethics that will be of interest to anyone working in, or with an interest in, criminal law, jurisprudence, penal theory, criminology, and moral and political philosophy.

The Search for a Unified Theory of Punishment

The fourth edition of Cybercrime and Digital Forensics provides a concise, cohesive exploration of all forms of cybercrime, including cyberterrorism and cyberwarfare, in an international context. This new edition includes:<ul> <li> A detailed chapter-by-chapter exploration of specific forms of cybercrime, ranging from hacking and malware to fraud to various sexual and interpersonal crimes and even online illicit markets;</li> <li>An updated discussion of criminological theories;</li> <li>Up-to-date examinations of the laws pertaining to cybercrime across the world, inclusive of Australia, Canada, the EU, India, the UK, and the US;</li> <li>Explanations of generative Artificial Intelligence (AI), with examples in each chapter of the ways AI is facilitating cybercrime and transforming the landscape of cybercrime regulation;</li> <li>A detailed history of digital forensics, as well as the current processes of evidence collection and analysis;</li> <li>Examples of real-life cybercrime, cyberterror, and cyberwarfare incidents from around the world.</li> </ul> This text is essential reading for courses on cybercrime, cyber-deviance, digital forensics, cybercrime investigation, and the sociology of technology.

An Introduction to Theory, Policy, and Practice

Cybercrime and Digital Forensics

Tech, War and the Fight for Humanity

Thundercloud

Haufe Fachbuch

In Zeiten von Gender Pay Gap, Fachkräftemangel und Generation Z benötigen wir faire, transparente und diskriminierungsfreie Entgeltsysteme. Bisherige Vergütungssysteme sind längst nicht mehr zeitgemäß, in denen soziale Kompetenzen und Belastungen vernachlässigt wurden. Die EU-Entgelttransparenzrichtlinie, die bis Juni 2026&nbsp; geschlechterneutrale Entgeltsystem vorschreibt, setzt dafür neue Standards.&nbsp;
Dr. Stefan Waschmann ist selbstständiger Berater für Entgeltsysteme und Vorkämpfer für "Fair Pay". Sein Buch hilft dabei, Schwächen in Vergütungssystemen zu erkennen, analysiert die durch die Entgelttransparenzrichtlinie erforderlichen Veränderungen und skizziert ein diskriminierungsfreies Fair-Pay-Gehaltssystem. Er versteht dabei die von der EU vorgegebenen Kriterien zur Funktionsbewertung als Chance. Diese bilden die Grundlage für eine Equal-Pay-Stellenbewertung, die heutigen Anforderungen wie Innovation, Anpassungsfähigkeit, psychosozialen Belastungen und sozialer Verantwortung gerecht wird.
Inhalte:
<ul><li>Der hartnäckige Gender Pay Gap</li><li>Bestandsaufnahme: die zerklüfteten Gehaltssysteme Mitteleuropas</li><li>Paradigmenwechsel Entgelttransparenz-/Lohntransparenzrichtlinie (ETRL)</li><li>Fair-Pay-Stellenbewertung: Grundsätze, Struktur und Kriterien</li><li>Die optimale Lohnkurve</li><li>Abgeltung atypischer Arbeitszeiten</li></ul>
Neu in der 2. Auflage:
<ul><li>Deutsches Gesetz zur Umsetzung der EU-Entgelttransparenzrichtlinie ab 2026</li><li>Umgang mit überdurchschnittlich bezahlten Mitarbeitern, deren Stellenbewertung höheres Gehalt nicht rechtfertigt</li><li>Wie Vergleichsgruppen zu bilden sind</li><li>Findung objektiver und geschlechtsneutraler Leistungskriterien</li></ul>

EU-konforme und diskriminierungsfreie Gehaltssysteme – die EU-Entgelttransparenzrichtlinie sicher umsetzen für mehr Lohngerechtigkeit, faire Vergütung und Chancengleichheit

Fair Pay

Aufzeichnungen einer jungen Köchin | »Ich liebe dieses Buch über alles – absolut köstlich.« Lena Dunham

Tart

Fusing High Tech with Human Touch for Organizational Success

The Pulse of Progress

Business Statistics of the United States

Business Statistics of the United States is a comprehensive and practical collection of data from as early as 1913 that reflects the nation's economic performance. It provides several years of annual, quarterly, and monthly data in industrial and demographic detail, including key indicators such as: gross domestic product, personal income, spending, saving, employment, unemployment, the capital stock, and more. Business Statistics of the United States is the best place to find historical perspectives on the U.S. economy. Of equal importance to the data are the introductory highlights, extensive notes, and figures for each chapter that help users to understand the data, use them appropriately, and, if desired, seek additional information from the source agencies. Business Statistics of the United States provides a rich and deep picture of the American economy and contains approximately 3,500 time series. The data are predominantly from federal government sources, including: ·Board of Governors of the Federal Reserve System ·Bureau of Economic Analysis ·Bureau of Labor Statistics ·Census Bureau ·Employment and Training Administration ·Energy Information Administration ·Federal Housing Finance Agency ·Department of the Treasury

Patterns of Economic Change

Business Statistics of the United States 2026

Strategies for Change

Confronting Legacies of Injustice

Skills for Scholars

Thoughtful advice on how to leave academia gracefully and build your best life in retirement Retirement is one of the most challenging transitions in an academic's career, and it's natural to feel overwhelmed by the changes that lie ahead. This how-to guide explains how to structure your last few years of employment so that you retire well and feel good about it. Drawing on engaging personal stories from across academia, it shares concrete tips for letting go of one key phase of life and embracing the opportunity to reinvent yourself in the next. On Retiring makes the case that you have the ultimate say in charting your path through retirement, aging, and whatever comes next after academia--and provides the guidance you need to do so. Susan Shaw describes the lessons she learned from her own retirement experience and those of her colleagues, highlighting what worked and what didn't while paying special attention to the things that make the academic workplace unique. She outlines the four-year retirement plan she developed for herself and suggest some steps colleges and universities can take to honor the service of faculty members and help them to stay connected after retirement. Along the way, Shaw examines some of the downsides of aging in the academy and discusses relevant differences in academic experiences, covering topics such as gender, race, and sexuality. Focusing on so much more than just financial planning, On Retiring empowers you with social, psychological, and philosophical tools to leave the academy on your own terms and thrive in retirement.

A Guide to Preparing for Life After Academia

On Retiring

Palgrave Studies in Equity, Diversity, Inclusion, and Indigenization in Business

Fostering Inclusivity and Well-Being

Embracing Diversity in the Workplace and Beyond

Chapman & Hall/CRC Texts in Statistical Science

From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian probability, statistical learning, and deep neural networks into a coherent intellectual framework. Whether you seek to understand why large language models hallucinate, how recommendation systems predict your preferences, or what makes reinforcement learning agents master complex games, this book equips you with both the theoretical foundations and practical intuitions that define the modern AI playbook.Key Features:<ul> <li>Builds Bayesian reasoning from first principles through historical examples like submarine search and WWII code-breaking</li> <li>Bridges classical statistics and deep learning, connecting linear regression to transformers</li> <li>Covers the complete AI stack: probability, decision theory, Gaussian processes, neural networks, CNNs, NLP, and LLMs</li> <li>Emphasizes uncertainty quantification-building systems that know what they don't know</li> <li>Practical applications across finance, healthcare, operations, and autonomous systems</li> <li>Emerging topics: AI agents, RLHF, and retrieval-augmented generation</li> </ul>Written for graduate students, data scientists, and quantitatively-minded practitioners, this book assumes comfort with calculus and basic probability while building sophisticated intuitions progressively. Business analysts will appreciate the decision-theoretic framing; engineers will value the architectural insights; researchers will find rigorous foundations for further study. Whether used as a course textbook, professional reference, or intellectual companion for understanding the AI revolution transforming every industry, this book delivers the rare combination of mathematical depth and accessible exposition that makes complex ideas genuinely understandable.

Foundations of Data Science

Bayes, AI, and Deep Learning

Sex Estimation of the Human Skeleton

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