Category: intersectionality

Today morning I woke up to this message in FSCI‘s chat room:

What happens here when a member reveals themselves to be a transphobe in another room? 🤔

I immediately said “COC applies”. The FSCI code of conduct, which I have contributed to the making of, is very clear about keeping FSCI an inclusive space. It explicitly recognizes that gender identity and expression can be diverse. And someone gets called a “transphobe” typically when they go against this idea.

But then there was this other question that came up in my mind. Would FSCI’s code of conduct apply to another room?

My first instinct was to read through the actual code and look at the sections where it discusses the scope of the code: “all of this community’s spaces, including public channels, private channels and direct messages, both online and off.” There could be an argument on technicality as to whether another room could be considered as community’s space. There could even be a counter argument that the mere presence of another FSCI member in the other room makes it a private channel thus bringing it under the scope of the code.

But I quickly realized where my “COC applies” comment came from. I wasn’t relying on technicality. I was relying on what I’ve internalized as the way a code of conduct works, and the way we influence others in the social organization.

And that has got a lot to do with being comfortable with the non-binary mess.

I was not like this earlier. I used to be very black and white, all or none about laws. I used to find comfort in the idea that anything human could be codified. Not just facts and information, but also implicit assumptions, emotions, social rules, and so on. So much so that I used to even think about building AGI with just symbolic AI through a comprehensive compilation of all these codified knowledge.

But as I started learning more about the world and interacting with human beings in the “real” world, I started recognizing that many things about human society is much more complicated than what could be codified. I’m not talking about this being quantitatively so large that it is too difficult to codify. It is complexity on a whole different dimension that prevents codification.

This complexity probably comes from free will. But what it practically amounts to is that there is no way to absolutely predict how human beings behave. (I leave it to the readers to draw parallels between this and quantum physics).

This particular understanding manifests in two different ways in my thinking: intersectional and non-binary.

I see the world in a heavily intersectional lens. Intersectionality is a framework that captures the many complexities of the world very well. It allows one to deconstruct (to use a word I used to hate) what’s happening without resorting to simplistic/reductionist explanations.

But intersectionality without an understanding of the non-binary is a dangerous pitfall. Often what I see people doing is to think of intersectionality in a binary way, wherein instead of having a yes or no explanation, they would have a yes or no + yes or no + yes or no explanation. They would just superimpose multiple explanations. Easier to explain with an example. I had (more than) once heard a description of how a person who is queer and Dalit and Muslim suffer from “triple oppression”. This sounds a lot like someone trying to add up binary bits. That’s the antithesis of intersectionality.

It is when you combine intersectional lens with a non-binary lens that you can see things more clearly and in more practical ways. In the non-binary lens not only do you see everything in shades of grey, you even see categories blurring. There’s no triple oppression when the very binary bits you are counting (Queer, Dalit, Muslim) cease to exist in well-defined boxes.

Sounds like a mess? It is a mess. Maybe I’m struggling to explain this, and that’s okay. But non-binary is when you’re comfortable with the mess. (Hat-tip to Swathi who attended the Looking In Looking Out Workshop and gave me the word “mess”)

Being comfortable with the non-binary mess is the key

Incomplete information, inadequate resources, limited time. These are three things that make humans humans as opposed to Gods who are omniscient, omnipotent, and omnipresent. We are doomed to live this way. And we might as well be comfortable with it.

The Code of Conduct is a good case study here.

There are some people who feel a code of conduct takes away freedom of speech. There are some who believe that it is best to leave the code of conduct very simple (“Be nice” folks). The FSCI code of conduct is rather long. It is a synthesis of many other similar codes.

What makes me comfortable with a code of conduct like this is that I see it as a non-binary mess. The CoC is an essay on a social contract that we aim to uphold. It codifies certain nuanced understandings of the world and demands people to grow those understandings. That is a certain kind of politics. And that is exactly how the world works. It is a constant negotiation of politics. There’s no clear way to categorize what it is. It is a mess.

The rules are rules. The rules aren’t rules. The rules apply to everyone equally. The rules don’t apply to everyone. The rules are clear. The rules are ambiguous. The rules ought to be respected. The rules can be changed. You can enforce the rules. You can’t enforce the rules. All of these things are true to various extent at various time in various contexts and situations. Everything is non-binary!

 So, does the CoC apply? It applies to the whole world!

Yesterday in a journal club at SOCHARA, we were faced with many challenging classification questions.

The paper we were discussing was titled “Metabolic non-communicable disease health report of India: the ICMR-INDIAB national cross-sectional study (ICMR-INDIAB-17)“. The second classification question was in the title. What is a “metabolic NCD”? Are there non-metabolic NCDs? The paper was only discussing diabetes and pre-diabetes, hypertension, obesity, and dyslipidaemia. What about things like stroke? MI? Cancer? Does the paper mean that these are not metabolic?

My explanation was that the study started out as a diabetes study, but expanded to others, and, to fit the word restrictions that journal format puts out, they came up with a word called “metabolic NCD” to refer to the subset of NCDs that were studied.

I searched on google scholar for any other reference to metabolic NCD and couldn’t find any other place where such a classification was being made. But on the WHO website, they classify the risk factors into two:

Modifiable behaviours, such as tobacco use, unhealthy diets, physical inactivity, and the harmful use of alcohol, all increase the risk of dying from an NCD.

Metabolic risk factors contribute to four key metabolic changes that increase the risk of NCDs: raised blood pressure; overweight/obesity; hyperglycemia (high blood glucose levels); and hyperlipidemia (high levels of fat in the blood). In terms of attributable deaths, the leading metabolic risk factor is elevated blood pressure, followed by raised blood glucose and overweight and obesity.

This language is repeated in Table 2 of the paper too where it refers to the prevalences of diabetes, prediabetes, hypertension, etc as: “Weighted prevalence of cardiometabolic risk factors among the study population”

What becomes clear is that categorizing NCDs into binary categories (like metabolic, not metabolic) is next to impossible. After all, nature doesn’t fit into neat categories. Every disease has metabolic risk factors. Every disease has behavioural risk factors. All things contribute to a disease to varying degrees. Rather than categorizing, it is better to think about how much the contribution of each is.

The next discussion was on the BMI cut-off used. In Europeans, only BMI above 30 is considered obesity, with BMI between 25 and 30 considered only as “overweight”. But WHO Asia-Pacific region recommendation based on studies from China, Singapore, India, etc is that cutoff 25 and above should be “obesity” in India. Above 23 can be considered overweight.

It was unclear why the cutoff of overweight could not have been used in this survey. At least, like “prediabetes” is quantified in the study, overweight could be quantified too such that we can anticipate an increase in obesity in the future.

Similarly for abdominal obesity, waist circumference of 90 cm above for “males” and 80cm above for “females” were used.

All these cut-offs are creating binary categories. The challenge with binary categories is that it does not account for the differences between people. By using different cut-offs you can account for some differences. (Like they account for race and sex above). But, those are not the only differences.

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