The myth of fake calls: #TheHardData
Organisation size: Small
Publication date: 8 Jun 2020
Credit: Juan Pablo Arredondo Reyes Retana
When thousands of women point out the same man for violence, the rest of the men question the credibility of all those voices and defend the rapist with tooth and nail.
Even if he has a history and we don’t even know him by sight, we shelter him in command because, deep down, we know the length of our own tail.
One of them was President Andres Manuel López Obrador, who, in a press conference and before the whole country, argued that 90% of the calls for gender violence to 911 were fake. But what does the hard data say?
In a context of pandemic and in which many women were forced to live with their aggressors during the isolation protocol, for the first time in the history of Mexico we were able to generate an accurate report of the “not appropriate” complaints, breaking them down into silent calls, non-emergency calls, incomplete calls, prank calls, insult calls, test calls, transfer calls and FAKE CALLS.
By disaggregating all the contacts to the 911 hotline, I identified that less than 0.58% of the calls were apocryphal, which places our country below the world average and helps to avoid both stigmatization and re-victimization of people attacked in am Mexico where 9 out of 10 crimes are not reported.
The study was replicated by national organizations such as “Me Too Mexico”, “We have other data” and “Ni Una Menos Mexico”, reaching up to 48,580 impacts (measurable and verifiable) that allowed to ratify that 1 of every 2 cases of violence against women emanates from the men they live with.
The most interesting impact of this report was that it received a cyber attack by organized machi-trolls and anti-rights groups on Facebook, which allowed me to identify 1,017 of those hate-inciting groups, causing them to permanently removed from the social network.
Likewise, it was possible to dispel the main myths expressed by López Obrador during the press conference and disprove a viral publication that circulated throughout Latin America during the pandemic entitled “Patriarchy? No little female friend, in Mexico there is no patriarchal society and I will explain why ”.
The most complex of these investigations was to analyze the 148 crimes contemplated by the National Census of State Justice Procurement, with victims and perpetrators, for 32 states of the Republic and full national compilation, generating a total of 9,768 variables.
Taking into consideration this volume of data, I generated an Excel formula that allows us to automate the exact disaggregation of men and women who are accused of crimes in the Mexican Republic, their degree of kinship with the person attacked, and the numerical proportion on territories with the highest crime incidence (per crime).
Once I automated these figures, it was quite easy to apply the principles of UN Women, Oxfam International, and CIMAC Press to build narratives with a gender perspective, modeling the indicators under a simple but powerful reading that directly impacts the language:
Because it is not the same to say that “33,981 women are sexually abused every year (as if they were asking for it)” to express that “31,558 MEN are raping young girls and women in a yearly-basis”.
Subsequently, I modelized the data with a non-sexist perspective using Adobe InDesign for distribution on social media, allowing me to generate master degree research’s in less than a week after the story exploded on the agenda-setting, maintaining novelty, temporality, and validity among digital communities to the extent that some of this data was used in iconoclasm and local protests all around the country.
What was the hardest part of this project?
The biggest challenge in this story was to create the Formula to cross the data of four different reports in an automated way: the National Statistics of the Number of Attention to Emergency Calls 911, the Information on violence against women (Crime incidence and emergency calls 911 ), the National Census of State Justice Procurement and Local Mobility Report on COVID-19 in Mexico, prepared by Google Inc.
Subsequently, it was required to structure a table of contents that would allow us to understand the increases during the pre-pandemic period and the increases generated during the “National Sana Distancia Day” until obtaining a single image that condensed three years of information in a single graph of pastry.
As stated in the Information Request 4010000000519 before the National Transparency Platform, not even the Mexican National Institute of Statistics and Geography has identified the existence of “crimes with convictions of women and men for false accusations after the acquittal/file of the denounced matter”.
And of course, consolidating this hard information, simplifying it for the general population, and without losing neither the instructional nor the methodology required, the manufacture of at least three Formulation Tables in record time (and even so, we published late).
What can others learn from this project?
If the COVID-19 pandemic has required us to do something, it is to learn new skills and abilities to “do more with less” in record time.
It is not necessary to have large newsrooms, budget increases, state-of-the-art technology, predictive tools, neural networks, and machine-learning protocols to tell stories that captivate our audiences, encouraging them to make the immediate transition to an increasingly just, empathetic, and informed world.
Very humbly, I allow myself to invite all of our invaluable information professionals to dare to “make things happen” and, from the powerful platform that social media provide us, launch in-depth investigations in real-time that will serve the public that really needs us: common men and women who are truth-thirsty in a country that ranks second in the world of #FakeNews distribution.
If a team of only one person can do it from a living room apartment, zero budget, and one-week deadlines with half a million impacts, I am sure that my colleagues, with much more preparation than myself, will be able to generate even more robust results.
Let’s make it digital, let’s make it simple, let’s make it quick, and, most importantly, let’s make it useful.