Isbn: 9781041357483 - from algorithms to evidence: using genai in evaluation practice (comparative policy evaluation) (9 resultados)

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  • Idioma: Inglés

    Editorial: Taylor and Francis Ltd, 2026

    1041357486 / 9781041357483

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Routledge, 2026

    1041357486 / 9781041357483

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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  • Idioma: Inglés

    Editorial: Routledge, 2026

    1041357486 / 9781041357483

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    • Primera edición

    Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.

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    Condición: New. 2026. 1st Edition. hardcover. . . . . .

  • Idioma: Inglés

    Editorial: Taylor & Francis, 2026

    1041357486 / 9781041357483

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    Librería: moluna, Greven, Alemaniamoluna

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    EUR 240,01

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    Condición: New. Kerry Bruce (DrPH) is a global health and evaluation practitioner working to support both practical monitoring, evaluation, and learning projects and training. She is the CEO of ClearUp Consulting and is a member of INTEVAL.Valentine Jos.

  • Idioma: Inglés

    Editorial: Routledge, 2026

    1041357486 / 9781041357483

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    Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore

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    EUR 353,43

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    Condición: New. 2026. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

  • Idioma: Inglés

    Editorial: Taylor & Francis Sep 2026, 2026

    1041357486 / 9781041357483

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    EUR 337,00

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    Buch. Condición: Neu. Neuware - From Algorithms to Evidence: Using GenAI in Evaluation Practice offers a timely, practice-grounded guide for evaluators and development professionals navigating the fast-moving world of generative AI. Building on the foundations laid in Artificial Intelligence and Evaluation (2025), this volume moves decisively from theory to application. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked but also what failed, why, and under what conditions. The result is a clear, practitioner-centered resource that cuts through hype and provides grounded, real-world insight.Structured around the seven phases of the evaluation lifecycle (design, structuring and inception, data collection, data analysis, reporting, judgment, and utilization), this book offers concrete examples of how GenAI is being integrated into everyday evaluation tasks. Contributors explain their rationale for using AI tools, the steps they took, and the results they achieved. Crosscutting chapters synthesize lessons on methodological adaptation, evolving evaluator competencies, and the ethical and professional standards needed to use GenAI responsibly. Throughout, this volume emphasizes 'hybrid intelligence,' showing how human expertise and AI-enabled methods can work together to strengthen evaluative reasoning.Clear, accessible, and grounded in real practice, From Algorithms to Evidence fills a critical gap in the literature. It provides evaluators, policymakers, and organizational leaders with practical guidance for building more adaptive, data-informed, and future-ready evaluation systems while keeping equity, transparency, and human judgment at the center of their work.…

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1041357486 / 9781041357483

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    Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    EUR 224,06

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    Hardcover. Condición: new. Hardcover. From Algorithms to Evidence: Using GenAI in Evaluation Practice offers a timely, practice-grounded guide for evaluators and development professionals navigating the fast-moving world of generative AI. Building on the foundations laid in Artificial Intelligence and Evaluation (2025), this volume moves decisively from theory to application. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked but also what failed, why, and under what conditions. The result is a clear, practitioner-centered resource that cuts through hype and provides grounded, real-world insight.Structured around the seven phases of the evaluation lifecycle (design, structuring and inception, data collection, data analysis, reporting, judgment, and utilization), this book offers concrete examples of how GenAI is being integrated into everyday evaluation tasks. Contributors explain their rationale for using AI tools, the steps they took, and the results they achieved. Crosscutting chapters synthesize lessons on methodological adaptation, evolving evaluator competencies, and the ethical and professional standards needed to use GenAI responsibly. Throughout, this volume emphasizes hybrid intelligence, showing how human expertise and AI-enabled methods can work together to strengthen evaluative reasoning.Clear, accessible, and grounded in real practice, From Algorithms to Evidence fills a critical gap in the literature. It provides evaluators, policymakers, and organizational leaders with practical guidance for building more adaptive, data-informed, and future-ready evaluation systems while keeping equity, transparency, and human judgment at the center of their work. This book offers a timely, practicegrounded guide for evaluators and development professionals navigating the fastmoving world of generative AI. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked, but also what failed, why, and under what conditions. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1041357486 / 9781041357483

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    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    Condición: Nuevo

    EUR 264,75

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    Cantidad disponible: 1 disponibles

    Hardcover. Condición: new. Hardcover. From Algorithms to Evidence: Using GenAI in Evaluation Practice offers a timely, practice-grounded guide for evaluators and development professionals navigating the fast-moving world of generative AI. Building on the foundations laid in Artificial Intelligence and Evaluation (2025), this volume moves decisively from theory to application. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked but also what failed, why, and under what conditions. The result is a clear, practitioner-centered resource that cuts through hype and provides grounded, real-world insight.Structured around the seven phases of the evaluation lifecycle (design, structuring and inception, data collection, data analysis, reporting, judgment, and utilization), this book offers concrete examples of how GenAI is being integrated into everyday evaluation tasks. Contributors explain their rationale for using AI tools, the steps they took, and the results they achieved. Crosscutting chapters synthesize lessons on methodological adaptation, evolving evaluator competencies, and the ethical and professional standards needed to use GenAI responsibly. Throughout, this volume emphasizes hybrid intelligence, showing how human expertise and AI-enabled methods can work together to strengthen evaluative reasoning.Clear, accessible, and grounded in real practice, From Algorithms to Evidence fills a critical gap in the literature. It provides evaluators, policymakers, and organizational leaders with practical guidance for building more adaptive, data-informed, and future-ready evaluation systems while keeping equity, transparency, and human judgment at the center of their work. This book offers a timely, practicegrounded guide for evaluators and development professionals navigating the fastmoving world of generative AI. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked, but also what failed, why, and under what conditions. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1041357486 / 9781041357483

    • Tapa dura
    • Impresión bajo demanda

    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    Condición: Nuevo

    EUR 258,68

    Envío por EUR 43,02 
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    Cantidad disponible: 1 disponibles

    Hardcover. Condición: new. Hardcover. From Algorithms to Evidence: Using GenAI in Evaluation Practice offers a timely, practice-grounded guide for evaluators and development professionals navigating the fast-moving world of generative AI. Building on the foundations laid in Artificial Intelligence and Evaluation (2025), this volume moves decisively from theory to application. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked but also what failed, why, and under what conditions. The result is a clear, practitioner-centered resource that cuts through hype and provides grounded, real-world insight.Structured around the seven phases of the evaluation lifecycle (design, structuring and inception, data collection, data analysis, reporting, judgment, and utilization), this book offers concrete examples of how GenAI is being integrated into everyday evaluation tasks. Contributors explain their rationale for using AI tools, the steps they took, and the results they achieved. Crosscutting chapters synthesize lessons on methodological adaptation, evolving evaluator competencies, and the ethical and professional standards needed to use GenAI responsibly. Throughout, this volume emphasizes hybrid intelligence, showing how human expertise and AI-enabled methods can work together to strengthen evaluative reasoning.Clear, accessible, and grounded in real practice, From Algorithms to Evidence fills a critical gap in the literature. It provides evaluators, policymakers, and organizational leaders with practical guidance for building more adaptive, data-informed, and future-ready evaluation systems while keeping equity, transparency, and human judgment at the center of their work. This book offers a timely, practicegrounded guide for evaluators and development professionals navigating the fastmoving world of generative AI. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked, but also what failed, why, and under what conditions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…