Media

Data vs Data – is India really ‘Lynchistan’?

In the recent Lynchistan debates, the data assembled by the scientist and writer Anand Ranganathan was quoted widely, on TV and social media, to dispel the fake Lynchistan narrative. A counter set of data, being repeated ad-nauseum these days, uses reports in the English language media as raw data (data set included reports from unreliable websites like Catch News, whose journalists have been caught spreading fake information many times) to prove that there indeed is a rise in cow related violence.

This is most absurd enough use of data, because the main criticism of those who disagree with branding the country as Lynchistan, is that the narrative is being pushed by the English language media, which has inherent bias against a particular ideology and thus it is wired to churn out biased reports.

To suggest that this media bias is some “conspiracy theory” is as naïve as believing that government is never wrong. It is not rocket science to realise that the mainstream media has a “liberal” bias. So much so, that renowned thinker and media critic Noam Chomsky once said that “if the system functions well, it ought to have a liberal bias” (emphasis added).

Almost every journalist identifies himself or herself as “liberal” and flaunts this identity and swears by this allegiance. There have been open admissions that the media used to “downplay” various incidents earlier, lest it leads to communal tensions – something television journalist Rajdeep Sardesai refers to as “moral compass”. The same Sardesai had given “political context” to killing of a person who was saving cows and virtually termed it a lesser crime when compared to killing of a person who wants to eat a cow.

The question is not whether the mainstream media has a “liberal bias” – it obviously has, and it is so as a matter of ingrained principle – but what does being “liberal” mean in India. And that’s is an open and relevant debate.

At OpIndia, our belief is that liberalism has been corrupted beyond recognition in India, with the mainstream media leading this “corruption”. Therefore, any research or analysis based on trends in news reports churned out by the same biased media is pointless. Such conclusions are as good as result of any Twitter poll.

However, that leads to a valid counter question that if we are not ready to accept a conclusion based on biased English language media reports, why should we accept the arguments made by Anand Ranganathan, who also used the reports by the same media.

On our part, we did not see him throw any numbers or graphs – as the other “research” articles are doing – to back his claim. His moot point was that mob lynchings – including cow related and communal ones – was hardly a new phenomenon that saw “alarming” rise under Modi.

Still, we asked him to elaborate on why he felt there was a need for this data and what this data actually meant. Following is his response.

Anand Ranganathan:

The whole point of my collecting rudimentary data was:

  1. To quickly counter the view professed by a journalist that a dozen odd lynchings in 3 years make India now Lynchistan. If they did, then dozen odd lynchings in 2012 and 2013 should have made India Lynchistan as well. Moreover, many of these lynchings were communal and caste-based in nature, and many were carried out by Muslim mobs.

For example:

  1. To explain in detail – 15 points – why the Lynchistan narrative is specious, both on account of data, and logic.

Here:

And here:

  1. To show that there occurred in just one year (2016) more than two dozen Muslim mob attacks, to dispel the notions of Islamophobia and exclusive attacks on Muslims, the two primary reasons why Media quickly began branding India Lynchistan.

Here:

  1. To show that the IndiaSpend data was non-normalised.

Here:

  1. To explain that purely in data terms, basically, all this data is noise, not signal. 60 odd attacks in 7 years, that too non-normalised data, cannot be anything else but noise in a population of 1.3 billion. On top of it, if this figure is not normalised with respect to to population and vocation, as I point out here, it doesn’t mean much. For example, if 2 incidents happened in 2013 and 4 happened in 2014, can we shout from the rooftops that 2014 saw a 100% increase in such incidents? Sure, technically, one would be right in saying so, but in my opinion, it would be alarmist to assert this, in a nation where every year there occur more than 60,000 communal incidents involving all communities. The same non-normalisation methodology for cow-related incidents has been followed in an article recently published in ORF blog. Signal Vs Noise distinction and normalisation is crucial and elementary for any meaningful interpretation.
  1. To show that data based exclusively on English news media reports cannot be the basis for reaching a definitive conclusion, given the obvious bias in the media as well as given that not all news is reported by the English news media. As people discovered in 2014-15, tens of temple thefts and robberies were reported in regional and other language media but not in the mainstream English media. Had it been, the scaremongering on account of church vandalism and robberies could have been quickly nipped in the bud and not taken 3 weeks to do so. And as people are finding out now, multiple instances of mob violence perpetrated by the Muslim community on account of goat theft was reported in non-English media but never found its way into the mainstream English media. Therefore, at best, such data is useful only to quickly point out the hypocrisy of some, or to provide quick counter arguments that themselves are based on such data.

As succinctly put here:

  1. To show that given the noise/signal point of above, and non-normalisation of data, and the fact that more than 2 dozen incidents of mob violence occurred in 2016 where the mob belonged to the Muslim community (just 1 year), it would be unwise to link scaremongering/hate speeches/anti-community sentiment, with the actual occurrence of the crime itself. Some of these issues have been addressed in point 2. Another interesting question that also arises if one were to think thus, is the following: UPA2 saw an 18% increase in crimes against Dalits. [In one year alone, 2012, 5 Dalits were raped every day.] Now would one assume that this astonishing increase was because the Cong professed anti-Dalit sentiment? I don’t think that they did. So then why did the crime increase? And here we aren’t talking of a dozen odd attacks to make a conclusion; we are talking of enough volume in data terms, tens of thousands of crimes, for us to be able to make a sound conclusion.

Nonetheless, I am happy that my tweets have led people to focus on data and its use in the media.

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