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Catalogue complet

Ridley J: Health and Safety in Brief

Health and Safety in Brief

Part 1 Part 1: Law; Chapter 1 Legal Processes; Chapter 2 Health and Safety Laws; Part 2 Part 2: Management; Chapter 3 Management Responsibilities; Chapter 4 Human Resources; Chapter 5 Workplace Safety; Chapter 6 Information and Advice; Chapter 7 Accidents; Part 3 Part 3: Occupational Health; Chapter 8 The body; Chapter 9 Health at Work; Chapter 10 Health Protection; Part 4 Part 4: Safety Technology; Chapter 11 Chemicals; Chapter 12 Noise and Hearing Protection; Chapter 13 Work Equipment; Chapter 14 Construction; Chapter 15 Manual Handling; Chapter 16 Mechanical Handling; Chapter 17 Safe Use of Electricity; Chapter 18 Fire; Chapter 19 Environment;

This book presents competitive trade models to recast them from the perspective of an economy which is beset with corruption and related intermediation that requires some sort of cost. It innovatively transforms traditional models (HOSV, SFM, HO nugget) by treating intermediation as a distinct economic sector that consumes factors of production.Through rigorous general equilibrium analysis, it also discusses real life events such as trade liberalization, capital inflow, labor immobility, extortion, etc. It is unquestionably an exciting approach to paving the way for future research around trade and development in competitive trade models befitting developing economies where ramifications of corruption and related damages are pervasive.This book will be of interest to researchers, faculty members, and policy makers working with international trade theory and policy, development economics and labour economics.

A Corrupt Economy Perspective

Rethinking Competitive Trade Models

In a world where machines learn, evolve, and sometimes outthink us, Artificial Intelligence and Safety offers a rare, integrated lens into both the power and peril of intelligent systems. Drawing on the authors' unique blend of programming mastery and enterprise risk leadership, this guide is your compass in the age of intelligent machines.This book goes beyond traditional risk management frameworks by integrating the latest advancements in artificial intelligence (AI) and generative AI. Combining real-world case studies, Socratic questioning, and the wisdom of AI governance pioneers, it journeys through the evolution of AI, the rise of deep learning, and the practical implications of large language models (LLMs) and retrievalaugmented generation (RAG). The authors translate complex technical knowledge into actionable insights and teach how to use Python not just for prediction, but for protection-turning code into a risk management ally. Readers will understand how to embed ethics by design, assess emerging risks, and confidently apply AI governance frameworks.This guide demystifies AI for everyone-from software architects to policymakers and risk managers. Whether you're crafting LLMs or setting enterprise policy, this book empowers you to not only ask the right questions but build the right systems, because the future of AI isn't just about building intelligence, it's about building it responsibly.

A Practical Guide for Programmers and Decision Makers

Artificial Intelligence and Safety

Enclosure Fire Dynamics, Second Edition

Security, Audit and Leadership Series

Corporate governance is failing-not because boards lack intelligence, experience, or diligence, but because the systems they rely on no longer surface the information that truly matters.Across industries and jurisdictions, boards approve strategies, review risk lists, receive assurance reports, and comply with governance codes-yet remain blindsided by catastrophic failures. Safety collapses. Cultural scandals erupt. Financial integrity breaks down. Courts increasingly ask the same question after the fact: Why didn't the board know?Mission Critical Governance exposes the root cause of this failure: boards govern without a clearly defined purpose and without reliable oversight of the mission-critical objectives that determine enterprise survival and success.Drawing on decades of governance practice, landmark court decisions, behavioural science, and emerging regulatory expectations, this book challenges the dominant "checklist" model of governance and replaces it with a new architecture built for uncertainty. It introduces a practical, evidence-based framework that enables boards to:<ul> <li>Define and disclose board purpose with clarity and accountability</li> <li>Identify and oversee Mission-Critical Objectives (MCOs) </li> <li>Quantify and report uncertainty using Acceptable / Unacceptable Uncertainty thresholds</li> <li>Measure confidence in information through the Board Assurance Index (BAI) </li> <li>Integrate risk, assurance, culture, and performance into a single oversight system</li> <li>Break the destructive Don't Tell / Don't Ask governance syndrome</li> </ul>This is not a compliance manual. It is a redesign of governance itself-from ritual to responsibility, from risk lists to real oversight, from comfort to confidence.Written for board directors, executives, regulators, investors, auditors, and risk leaders, Mission-Critical Governance provides a clear roadmap for transforming governance into a disciplined, purpose-anchored system capable of earning trust, withstanding scrutiny, and guiding organizations through an era of relentless uncertainty.The question is no longer whether boards must govern differently. The question is whether they will lead-or wait for courts, crises, and capital markets to force the change.

Focusing on What Matters Most

Mission-Critical Governance

Young Voices and Future Choices in Australia, the United Kingdom and Japan

Gender, Work and Care

Why does gender inequality persist in tech-even in workplaces that invest in fixing it? In Networking to Nowhere, sociologist Ethel Mickey uncovers the paradox at the heart of modern tech culture: Networking is hailed as the key to opportunity, yet it systematically works against women. Drawing on ethnographic research inside a top tech firm, Mickey reveals how "ideal" networking practices like informal referrals, after-hours schmoozing, and bro-bonding over sports reinforce old boys' clubs that exclude women and people of color. Women, encouraged to lean into formal events, conferences, and diversity programs, often find these efforts go unrewarded, networking them to nowhere. By exposing how gendered expectations, invisible cultural codes, and even well-meaning corporate DEI programs can deepen inequality, this book offers a powerful new framework for understanding gender and organizations in the contemporary economy-and what it will take to chart a new path forward.

How Gender Inequality Persists in Tech

Networking to Nowhere

Bringing together essays from neurodivergent and disabled writers, and writers with chronic illnesses, this collection explores the impact of these experiences and the struggle against such biases within the field of creative writing. Whilst neuro-divergent and disabled writers publish world-class poetry, prose, and drama that moves readers and wins awards, they face many difficulties accessing these achievements - difficulties which often go unnoticed, unmentioned, and underappreciated. Visibility, insight, alternative approaches, and thorough research are all needed to create more inclusive writing environments. This book confronts these issues head on, calling for diversity in the creative writing field, community, and industry, and more equitable spaces in adjacent arenas from academia to publishing. Broken into four sections, this anthology focuses on creative writing programs, classrooms, the community, and its people, combining narrative, research and practical contributions to the field to offer a mix of practical strategies, personal and pedagogical interventions, critiques, and craft meditations that explore teaching, transformation, evolution, embodied craft, visibility, belonging, injustice, otherness, and views from the outside. With essays and excerpts written by authors and educators from across seven countries, who are each impacted by a wide range of disabilities, including ADHD, autism, blindness, dyslexia, dyspraxia, stroke aphasia, cerebral palsy, bipolar, fibromyalgia, and rheumatoid arthritis, this collection informs, deconstructs and re-imagines to reform and revolutionize normative structures within writing institutions and communities.

Disability, Illness, Neurodivergence, and Ableism in Creative Writing

Divergent Writers

A Norton Short

How Household Employers Exploit Domestic Workers

The Trafficker Next Door

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

The Deep Learning Revolution

Employment, Hours, and Earnings

A special edition to the Handbook of U.S. Labor Statistics: Employment, Earnings, Prices, Productivity, and Other Labor Data, this reference is a consolidated wealth of employment information, providing monthly and annual data on hours worked and earnings made by industry, including figures and summary information spanning several years.These data are presented for states and the 75 largest metropolitan statistical areas (MSAs).

This edition features:

- Nearly 300 tables with data on employment for each state, the District of Columbia, and the nation's seventy-five largest MSAs

- Detailed, non-seasonally adjusted industry data organized by month and year

- Ranking of the seventy-five largest MSAs

- Concise technical notes

- A comprehensive appendix 

The employment, hours, and earnings data in this publication provide a detailed and timely picture of the fifty states, the District of Columbia, and the nation's seventy-five largest MSAs. These data can be used to analyze key factors affecting state and local economies and to compare national cyclical trends to local-level economic activity.

This reference is an excellent source of information for analysts in both the public and private sectors. Readers who are involved in public policy can use these data to determine the health of the economy, to clearly identify which sectors are growing and which are declining, and to determine the need for federal assistance. State and local jurisdictions can use the data to determine the need for services, including training and unemployment assistance, and for planning and budgetary purposes. In addition, the data can be used to forecast tax revenue. In private industry, the data can be used by business owners to compare their business to the economy as a whole and to identify suitable areas when making decisions about plant locations, wholesale and retail trade outlets, and locating a particular sector base.

States and Areas

Employment, Hours, and Earnings 2025

A shocking 90% of start-ups fail. Many of these failures are preventable, but you need to understand the causes and how to avoid them - both as an entrepreneur and an investor. From technology to the market, from leadership to money, there are numerous reasons why your start-up will fail. Bernie Bulkin - who has been at both sides of the investment table - guides you through the six major reasons why start-ups fail, and how to avoid them. Instead of accepting failure as inevitable, this book breaks down the main reasons why start-ups fail and how to turn them on their head. Whether you're a founder or an investor, if you're going to put in the time, money, and effort to ensure a company succeeds, you should go in with your eyes open. Bernie's common-sense approach offers the experience of a venture capitalist who has been there and done that. Leadership at all levels makes a difference. Using real-life examples, and applying behavioural economics to venture decision-making, Why Start-Ups Fail spotlights what founders most often lack, and shares the who, how, and why of making a start-up succeed and avoiding the traps blocking your path to commercial success.

Avoiding the traps on the path to commercial success

Why Start-Ups Fail

A Comprehensive Approach to Developing a Sustainable System

Safety Management

Health and Safety in Brief

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