Q&A with Rukmini Srinivasan | India News – Times of India

‘Misuse of data is a bigger problem than manipulation’

If you like to think of yourself as middle class and want to Maintain it Don’t read about the illusion, ‘Whole Numbers and Half Truths: What Data Can’t Tell Us’ Modern India’. Written as a “tool-kit for India” by data journalism pioneer Rukmini Srinivasan, it breaks down the nation’s heated assumptions through cold official data about everything from love to food and marriage to elections. Is. In an interview, the freelance journalist, who has been investigating the country through numbers since 2010, Sharmila Ganesan tells Ram about the dangers of data being discarded, misread and misused.

can you share something dear narrative That data counter about India?

People like to believe that caste doesn’t matter to voters as they say they are voting for jobs and development, but at the same time 45% of voters want an MP who belongs to their caste. Very Enough Rich people like to assume they belong to the middle class, but anyone in urban India who spends more than Rs 8,500 would be in the top 5 percent of the country. It is believed that Muslims have high fertility rate, but the fertility of Muslim women in the southern states is lower than that of Hindus in the Ganga belt states. Young people often hold more socially conservative views than older people. Marriage is still almost entirely within caste and arranged in India.

Exactly how poor is the great Indian middle class today?

Nothing loves rich Indians more than thinking that they belong to the middle class. The real middle of the country is basically poor. By 2011-12, if India was divided into five classes of equal size in terms of income, the middle 20 percent of Indian households would earn between Rs 55,000 to Rs 88,800 a year. Only 40 per cent of the top two sections had piped water and only 15 per cent got water for three hours a day. More than half had flush toilets and half had access to electricity for eighteen hours a day – a scenario we imagine middle-class life would be like. Even as recently as 2017-18, we know from the data hidden by the government that only between Rs 2,700 and Rs 3,600 per month was spent in the middle of urban India. As I have suggested in the book, we need our own terminology and classification for the Indian middle class.

What are some of the biggest news stories that Indian media have missed or underestimated despite the numbers?

The Indian media has been guilty of both underestimating and underestimating the Indian growth story – data and on-ground evidence of slowing real growth in income and acute deprivation among certain groups in the early 2000s as well as more recently. Both were, but that story was briefly missed. Equally, the major reductions in poverty in the late 2000s and early 2010s were not talked about enough. In the last two years, the missing figures of Covid deaths in India have been quite strong and
Obviously, but a large section of the Indian media has downplayed the story.

There is growing suspicion in some sections about data manipulation. is it a concern

valid?

I approach most things – including data – with healthy skepticism, but I discourage skepticism entirely. I think the evidence is that the data is under great stress – there are documented delays in official data, and an official survey on household consumption expenditure was suppressed. The official explanation was that the data was not good enough, but given that it followed previous conventions and has been reviewed, the most likely explanation is that the government buried it because it was ineffective. So the issues there were sidelined and suppressed rather than manipulative. Right now, I think the propagation of data is a bigger problem than the manipulation of actual data.

What did COVID teach us about the dangers of misreading data?

The pandemic showed us, for one, the need to build data structures in “peace-time” so that we have the tools we need in a crisis, and not trying to strategize in an emergency without the most basic understanding of disease. of mobility and health infrastructure. It also showed us that sitting and resting should not be the basis for a country with low numbers, where almost no section of the data has full registration.

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