Invisible Women: Exposing Data Bias in a World Designed for Men ( Kindle ePUB or Ebook ) ↠ vansoutletmall.co.uk

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?s livesFrom government policy and medical research to technology workplaces urban planning and the media Invisible Women reveals the biased data that excludes womenAward winning campaigner and writer Caroline Criado Perez brings together for the first time an impressive range of case studies stories and new research from across the world that illustrate the hidden ways in which women are forgotten and the impact this has on their health and well being In making the case for change this powerful and provocative book will make you see the world ane. The eight intelligent strong independent women ages 45 to 61 in our reading Group read this and found were strongly against the tide of opinion in the reviews thus far We all found it biased tedious one sided and generally without a balanced view of the topics covered Some conclusions were just plain preposterous ridiculous and sometimes funny eg bricks being made smaller to fit women s hands There were some nuggets in there around women s health and safety issues but they were almost lost in the mountain of stats bias ironically and negative rhetoric The tone was at times desperate aggressive hurried and it provoked anger amongst some of our members Would not recommend to anyone Sottomissione new research from across the world that illustrate the hidden ways in which women are forgotten and the impact this has on their health and well being In making the case for change this powerful and provocative book will make you see the world ane. The eight intelligent strong independent women ages 45 to 61 in our reading Group read this and found were strongly against the tide of opinion in the reviews thus far We all found it biased tedious one sided and generally without a balanced view of the topics covered Some conclusions were just plain preposterous ridiculous and sometimes funny eg bricks being made smaller to fit women s hands There were some The Isles negative rhetoric The tone was at times desperate aggressive hurried and it provoked anger amongst some of our members Would KING not recommend to anyone

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 Invisible Women: Exposing Data Bias in a World Designed for Men

THE #3 SUNDAY TIMES BESTSELLERDiscover the shocking gender bias that affects our everyday lives'A rallying cry to fight back' Sunday Times'Press this into the hands of everyone you know It is utterly brilliant' Helena Kennedy'A game changer; an uncompromising blitz of facts sad mad bad and funny making an unanswerable case and doing so brilliantlythe ambition and scope – and sheer originality – of Invisible Women is huge' The TimesImagine a world where your phone is too big for your hand where your doctor prescribes a drug that is wrong for yo. I bought this book intending it to be a gift for a family member We have a shared interest in statistics and this seemed like a good punt Unfortunately it will not be passed onFirstly the positivesThe author is clearly very passionate about her field and has put together a truly awe inspiring set of statistics that completely support the stance that women are biased against in society This clearly needs to change and there are some very good examples of where this could be done easily and effectively It has been an eye opener to me to consider some of the examples brought up crash test dummies drug testing and outdated sexist guidance in a number of areasThe negativesThere is a consistent pattern of stating a set of statistics and then expressing an opinion that this is an example of gender bias which could be fixed with gender disaggregated data On a first read the conclusions which seem consistently that men make decisions and that those decisions are implicitly designed to make women worse off off are not entirely supportable by the statistics gatheredAs an example snow sweeping which is carried out by clearing the main roads first and then minor roads The statement made is that this is biased against women as this benefits those commuting by car men and harms physically those who travel on minor roads as pedestrian women The conclusion that data should have been gathered which included women to prevent this bad decisionFirstly it could be plausible that the decision makers being commuters by car themselves might have made a decision based upon their experience This is in and off itself is decoupled from gender One could imagine a mixed panel of working men and working women making the same poor decision with eual gender representationSecondly the bias that exists seems to be that men benefit from the status uo than women due to the nature of the jobs they do paid work full time greater male proportion The imbalance here is not how streets are cleared but who the jobs are carried out by so addressing gender bias via the job market would be a better path to removing the gender bias without addressing the poor decision making of how to clear snowThirdly if one were to gather gender dis aggregated data this might incentivise eual gender participation However this does not guarantee that the set of people involved were from different selection groups and might still exclude those people that do not commute via main roads I am sure plenty of women also benefited from the main road first approach so one could imagine a poll of opinions which covers 5050 by gender but excludes non commutersAll of the above are independent on what the best way to clear snow is and what we even mean by best in this context cheapest for execution reducing road accidents reducing hospital attendanceI ve already fixated on this one example too much there are others but if you have read this far I risk boring you too much The issues raised in the book could probably accurately be expressed as a journey into poor decision making by excluding groups given selection bias The biases are not specifically gender and do not generally indicate a bias against women there are other biases and poor decision making at play that predominantly harm women as a side effect although there are also examples of terrible bias that deserve to be considered crash test dummies for everyone pleaseI think the author sets off with an axe to grind and spends the book grinding it If you are feminist or pro euality with a view that the world is biased there will be a lot to enjoy here If you attack it objectively there are still some gems with regards to systemic bias but there are plenty of opinions that do not bear up to analysisOverall a good book I think just lacking a level of objective scientific rigor that would have made it s message convincing

Review Invisible Women: Exposing Data Bias in a World Designed for Men

Ur body where in a car accident you are 47% likely to be seriously injured where every week the countless hours of work you do are not recognised or valued If any of this sounds familiar chances are that you're a woman Invisible Women shows us how in a world largely built for and by men we are systematically ignoring half the population It exposes the gender data gap – a gap in our knowledge that is at the root of perpetual systemic discrimination against women and that has created a pervasive but invisible bias with a profound effect on women?. Incredible book Brilliantly researched and backed up Easy to read not boring at all Read if you want to be miserable about the state of the world for women but also intelligent and having enjoyed a few jokes


10 thoughts on “ Invisible Women: Exposing Data Bias in a World Designed for Men

  1. says:

    First things first: the designer of this book was clearly on a roll. The font is clear and delightful. The italics, in particular, are so beautiful I had to take a picture of them and send it to my friend so he could appreciate them too. The cover design is subtle and fantastic. When you take the dustjacket off, the overlaid blue male figures disappear, leaving the invisible women behind, which ties in wonderfu

  2. says:

    I bought this book intending it to be a gift for a family member. We have a shared interest in statistics and this seemed like a good punt. Unfortunately it will not be passed on.

    Firstly the positives:
    The author is clearly very passionate about her field and has put together a truly awe inspiring set of stat

  3. says:

    This book is amazing at opening the door on invisible bias, unfortunately I am not a fan of the writing style.

    The author makes fantastic points backs it up with great facts but then in an attempt to cement her point she will suddenly and needlessly jump to unrelated examples of sexism e.g. she makes fantastic eye

  4. says:

    Incredible book. Brilliantly researched and backed up. Easy to read, not boring at all. Read if you want to be miserable about the state of the world for women but also intelligent and having enjoyed a few jokes.

  5. says:

    The brilliance in this book is that Criado Perez presents multiple examples of a blatant male bias in the aggregate data being used to make decisions that affect women and men and leaves it sitting there for all to see that acceptance of the status quo is untenable, for any progressive and healthy society. There is no m

  6. says:

    This is a very well written book which carefully exposes an extraordinary volume of missing data across every area of our lives. As a woman, wife, mother, former carer, it resonates. As an emerging technology specialist working on the fringes of machine learning and aware of data bias, it throws up huge implications for

  7. says:

    The eight intelligent, strong, independent women (ages 45 to 61) in our reading Group read this, and found were strongly against the

  8. says:

    Totally biased and circumstantial not worth reading

  9. says:

    This book was a complete disappointment. No insight provided beyond what is already known. The main purpose of the book appears to be how many times can you use / repeat the tag line ‘gender data gap’ before the reader wants to burn it. T

  10. says:

    An important, insightful book that everyone should make an effort to read, exposing, largely successfully, how 50% of the world's population is ignored in data modelling.
    However, it does need to be read critically, with

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