---
title: "Identity and positionality"
source: The Turing Way
source_url: https://github.com/the-turing-way/the-turing-way
licence: CC-BY-4.0
domain: data-and-analysis
subdomain: turing-way
date_added: 2026-04-25
---

(er-self-reflection-identity-positionality)= 
# Identity and positionality

Traditional science training may lead us to believe that it is possible to analyse and interpret data objectively.
This tends to be because most sciences, and data, are often seen as being inherently neutral. 
However, we know now that the way data is collected, recorded and used can create significant problems for fairness, accountability and bias in data science systems. 
For example, we might choose training data for a model without thinking to consider whether it is representative in a particular way, or we might not consider whether a data visualisation is accessible to people with color blindness. 

Some schools of thought say that true objectivity is impossible because every person comes with their own lived experiences. This provides the lenses through which we see the world and influences the way we behave, including how we do research. 
These could be 'macro' influences like our motivations to address a particular problem, or 'micro' like the way we numerically represent a social concept.  
While there are lots of benefits to the individual ways we all experience the world, the single view each person takes can also embed unseen biases into how we think and work. 

By better understanding ourselves, we can be more proactive about spotting where we might hold biases or gaps in our knowledge. 
This means we can be transparent about how our unique view has influenced the way we work, which is beneficial to scientific integrity and reproducibility. 
It can also help us to identify and work against systemic and structural barriers that might otherwise go unchallenged, in order to make our research environments more inclusive (see {ref}`Activism<er-activism>`).

The placement of our identities, socio-cultural position and epistemological approach [{term}`def<Epistemology>`] to knowledge in the context of our research is called our *positionality*.
We can understand our positionality through the practice of *reflexivity*, which is the process of using *self-reflection* [{term}`def<Self Reflection>`] to better understand how our identities and experiences influence the way we behave in our work. 

(er-self-reflection-social-graces)= 
## Understanding ourselves

Self-reflection and reflexivity can be challenging, and takes time and practice to feel natural.
To be most effective, they should be employed throughout our work and will never be 'finished' as we constantly change and so does the world around us.

In order to help get started, there are lots of frameworks that can be used as a guide.
One of these is called the 'Social Graces', which was developed by psychotherapists John Burnham, Alison Roper-Hall and colleagues in the 1990s {cite:ps}`burnham2018developments`.

The Social Graces are a mnemonic to help cover aspects of identity that affect our power and privilege.
They are not fixed and you can choose the most relevant ones, or add more.
The idea of the Social Graces was to explicitly name power differentials, which might be visible or invisible in our interactions. 

- **G** = Gender, Geography
- **R** = Race, Religion
- **A** = Age, Ability, Appearance
- **C** = Class, Culture
- **E** = Ethnicity, Education, Employment
- **S** = Sexuality, Sexual Orientation, Spirituality

The Graces are a helpful place to start thinking about your intersecting identities.

It can also be helpful to ask:
- Which of the Social Graces do I particularly identify with? Are there some that stood out to me right away?
- Which Social Graces did not stand out to me, and why might that be?
