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The Life of a Number : Measurement, Meaning and the Media /
Drawing on case studies, this book examines how politicians, academics and journalists gave meaning to data during the COVID-19 pandemic. Lawson sheds light on the distinct nature of the pandemic that led to the increased politicization of data and how it permanently changed the way we view health a...
| Autor principal: | |
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| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Bristol :
Bristol University Press,
2023.
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| Colección: | Book collections on Project MUSE.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Lawson, Brendan, |e author. | |
| 245 | 1 | 0 | |a The Life of a Number : |b Measurement, Meaning and the Media / |c B.T. Lawson. |
| 264 | 1 | |a Bristol : |b Bristol University Press, |c 2023. | |
| 264 | 3 | |a Baltimore, Md. : |b Project MUSE, |c 2023 | |
| 264 | 4 | |c ©2023. | |
| 300 | |a 1 online resource (166 pages). | ||
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| 505 | 0 | |a Front Cover -- The Life of a Number: Measurement, Meaning and the Media -- Copyright information -- Dedication -- Table of Contents -- 1 Introduction -- Data bound -- Chapter 2: Data bounds are reinforced by policy -- Chapter 3: Quantitative realism underpins data bounds -- Chapter 4: Quantitative realism is mathematical and abstract -- Chapter 5: Desire for data bounds underpins quantitative realism -- Chapter 6: Data bounds are emotive -- Chapter 7: Data boundaries are drawn within historical norms -- Chapter 8: Critically engaging with data bounds -- More cases, less theory | |
| 505 | 0 | |a The life of a number -- The pandemic in the UK -- 2 Data Bounds Are Reinforced by Policy -- Trade-Off -- Protect Both -- Short-term vs long-term data -- International comparisons -- The problems of comparing death tolls -- The problems of comparing Gross Domestic Product -- What about data outside the data bounds? -- Alternatives to Gross Domestic Product -- Excess deaths -- Beyond cases, hospitalizations and deaths -- How policy structures data bounds -- 3 Quantitative Realism Underpins Data Bounds -- Two metres -- 15 minutes -- How 'close contact' structured policy | |
| 505 | 0 | |a How numbers organize the unorganizable -- Binding together the sciences -- 4 Quantitative Realism Is Mathematical and Abstract -- Counting cleaning wipes -- Numbers as language -- The meaning of big numbers -- One billion items as political rhetoric -- Unprecedented crisis met with an unimaginable number -- The itemization of Personal Protective Equipment -- The four Personal Protective Equipment problems the figure tried to erase -- Lack of adequate stockpiles -- Inadequate production and procurement networks -- Prioritizing the National Health Service over social care | |
| 505 | 0 | |a Changing what classes as suitable Personal Protective Equipment -- The power of huge -- 5 Desire for Data Bounds Underpins Quantitative Realism -- Rethinking the infodemic -- Where was the 'mis-behaviour'? -- Trust us: we are not misinformation -- The life of both figures -- Surveys and 7 per cent -- Digital data and eight million -- A strategic emphasis on quantitative realism -- 6 Data Bounds Are Emotive -- Data visualization -- Representing the experience of the pandemic -- Turning death into a graph -- Performing data -- Performance norms in Sky News -- Sombre performance of death | |
| 505 | 0 | |a Flouting the convention -- Feeling data -- 7 Data Boundaries Are Drawn Within Historical Norms -- Red-herring of inaccurate projections -- Vaccines, cases and risk -- Normalizing health inequalities -- The failed campaign of the 'outsiders' -- 8 Critically Engaging with Data Bounds -- Pay attention to media and communication -- The media ecosystem -- Interrogate and appreciate quantitative realism -- Language, measurement and documentation -- The tail that wags the dog -- Examine how data bounds can maintain or challenge power -- Public health imperative -- Ethical purpose | |
| 520 | |a Drawing on case studies, this book examines how politicians, academics and journalists gave meaning to data during the COVID-19 pandemic. Lawson sheds light on the distinct nature of the pandemic that led to the increased politicization of data and how it permanently changed the way we view health and society more broadly. | ||
| 588 | |a Description based on print version record. | ||
| 650 | 7 | |a Medical informatics. |2 fast |0 (OCoLC)fst01014175 | |
| 650 | 0 | |a COVID-19 Pandemic, 2020- |x Mathematical models. | |
| 650 | 0 | |a COVID-19 Pandemic, 2020- |x Data processing. | |
| 650 | 0 | |a Medical informatics. | |
| 655 | 7 | |a Electronic books. |2 local | |
| 710 | 2 | |a Project Muse. |e distributor. | |
| 710 | 2 | |a Project Muse. |e distributor | |
| 830 | 0 | |a Book collections on Project MUSE. | |
| 856 | 4 | 0 | |z Texto completo |u https://projectmuse.uam.elogim.com/book/111864/ |
| 945 | |a Project MUSE - Custom Collection | ||
| 945 | |a Project MUSE - 2023 Complete | ||
| 945 | |a Project MUSE - 2023 Science, Technology and Media | ||