“Data abuse is a bigger problem than manipulation ‘if you like to think of yourself as a middle class and want to maintain an illusion, don’t read’ integers and half truth: what data can tell us about modern India ‘.
Written as” Tools -Alat for India “by Pioneer journalism data Rukmini Shrinivasan, it destroyed the warm idea of ​​the country about him through cold official statistics about everything from love and marriage with the election.
In an interview, independent journalists, who have examined the country through numbers Since 2010, tells Sharmila, Ganesan Ram about the dangers of dismissal, reading and misusing data can you share some of the beloved narratives about India calculated data? People like to believe that caste is not a problem for voters because they say they choose jobs and growth, but at the same time 45% of voters Wants a member of MP from their castes.
Many people who are quite rich like to believe that they are middle class, but anyone in urban India who spend more than RS 8,500 will be in the top 5 percent of the country.
Muslims are believed to have a high fertility rate, but Muslim women in the southern state have lower fertility than Hindus in the belt countries of the gangetic.
Younger people often hold more conservative social views than parents.
Marriage is still almost entirely in caste and is arranged in India.
Is it exactly how poor the Indian middle class today? Nothing is rich in Indians more loving than thinking of their middle class.
Mid-state is actually basically bad.
In 2011-12, if India was divided into five classes with the same size in income requirements, 20 percent of middle Indian households will get Rs 55,000-Rs 88,800 per year.
Only 40 percent of those in the top two classes have pipe water and only 15 percent get even three hours of water every day.
More than half has a flush toilet and only half gets eighteen electric hours in a day – a scenario is quite excluded from what we imagine for life.
Even recently 2017-18, we know from the data suppressed by the government that the central part of India spent between Rs 2,700 and Rs 3,600 per month.
As I suggest in this book, we need our own vocabulary and classification for the Indian middle class.
What has been some of the biggest stories that have been missed by Indian media despite the number? Indian media has been guilty of exaggerating and underestimating India’s growth stories – in the early 2000s also recently, both of them.
Data and land evidence slowdown in real growth in acute income and seizure among several groups, but the story is missed for a while.
Equally, a large reduction in poverty until the second half of the 2000s and early 2010 was not discussed enough.
In the past two years, data in India lost Covid’s death has been quite hard and clear, but most of Indian media have underestimated this story.
There are growing skeptics in certain parts of falsified data.
Is this worries valid? I approached most of the things – including data – with healthy skepticism, but I prevented the suspicion of blankets.
I think the proof is that the data is under great pressure – there is a documented delay in official data, and one official survey of household consumption expenditure is pressed.
The official explanation is that the data is not good enough, but given that he follows the past convention and has been examined, the most likely explanation is that the government buried it because it was unpleasant.
So the problem there puts aside and presses rather than manipulation.
At present, I think the misuse of propagandistic data is a bigger problem than actual data manipulation.
What is Covid taught about the danger of the wrong data? Pandemic shows us, for one, that the data structure needs to be built in “peace time” so we have the tools we need in a crisis, and do not try to form a strategy in emergency situations without the basic understanding of the dynamics of diseases and health infrastructure.
It also shows us that low numbers should not be accommodated to sit and relax in the country where there is no full registration in almost all statistical segments.