Data Day Reflective Blog
The data day was refreshing in the sense that we had some word play, and I wrote a Haiku on the spot which I didn’t think was possible, and never would have attempted it out of this context. It was also refreshing to meet some new faces, especially as I can’t get out of the house much these days.
This is my Haiku
Where are the papers
They’re all around the hard drive
Copy and delete
The presenters for this valuable workshop communicated clearly and facilitated a lively discussion that afternoon. The debate around the pros and cons of data was interesting. People’s annoyance with the way data was presented to the nation and the world regarding covid was interesting too. I guess some of the population really engaged with the detail in the covid data and formed a critical eye. The discussion on how covid data circulated during the pandemic highlighted to the group, the dangerous power of manipulating data and deliberately misrepresenting the truth, linking to fake news.
In our break out group we covered a bit of data collection purposes in teaching. My experiences here are that students enjoy presenting it once they have collected it as it makes their research come to life.
I reflected that we have our ‘common sense’, and often see very clearly what is going on around us, in a hermeneutic sense that Dyer (2010) explains is human’s everyday ‘practice of interpretation, where interpretation involves an understanding that can be justified’.
For justification, sometimes it is important to collect data to either substantiate our beliefs or to develop awareness of the cracks that run through them. Nonetheless, Vaditya (2018) highlights the importance being aware of the processes behind the social construction of knowledge, stating,
‘Epistemology is the philosophy of knowledge, which sets the parameters to as to what counts as knowledge, which can be considered as a refined version of common sense which happens to be the common (sense) of the dominant groups projected as natural truth’.
I think this means that we need to ask ourselves, who says what knowledge is, this agreed cache of facts, and whether it belongs to me, or is indicative of what I have experienced and interpreted of the world.
In the workshop a data example was presented, that reflected unfairness in student achievement across demographic groups. This then linked to unequal representation of demographic groups in senior jobs in higher education. The recent appointment of the vice-chancellor, for example, was considered a lost opportunity for the institution to take some initiative towards balancing representation, as is the recent appointment of LCF’s head of college.
The chat from our session reflected an objection to some specific terminology; I won’t use it here as that would just perpetuate negativity.
Terminology/language is data as well as numbers. And the issue raised in the chat from the workshop that day, reflects the importance of thoughtful and considered choices with using labels for group of people.
Following on from the data day, I discovered, more relevant in the US than the UK but still interesting to me, Hughes et al.’s (2016) article explaining why researchers study demographics which is to,
‘determine whether identity is causing an individual to do a specific thing (i.e., independent variable) or if something is causing an individual to adopt a certain identity (dependent variable)’.
This knowledge can then contribute to analysis of inequalities.
Hughes et al. (2016) argue for close attention to the language used to describe groups of people in order to capture more specific research results.
Something that caught my eye in Hughes et al. (2016) article, was that in the US, ‘the Census Bureau is considering using a new approach in 2020, which includes eliminating the terms ethnicity and race (Cohn, 2015)’, cited in Hughes et al. (2015).
So I checked it out, and there’s definitely race questions in the 2020 American census.
So much for that idea.
Returning to the Hughes et al. (2016) article, they
‘suggest this new approach, given in Figure 3, for researchers collecting data in the United States. This approach decreases the typical confusion created with the old categories and includes an updated list of categories with a new Middle Eastern and North African response category (Cohn, 2015)’.
I have pasted an example below of their Figure 3 which demonstrates providing sample participants in research studies with a richer choice of language of which to identify.
FIGURE 3 (Hughes et al., 2016).
Bringing the focus back to this side of the Atlantic, here are some recent recommendaitons from our UK government’s Commission on Race and Ethnic Disparities.
‘Recommendation 23: Use data in a responsible and informed way
Develop and publish a set of ethnicity data standards to improve understanding and information gathering, reducing the opportunity for misunderstanding and misuse’.
‘Recommendation 24: Disaggregate the term ‘BAME’
‘Stop using aggregated and unhelpful terms such as ‘BAME’, to better focus on understanding disparities and outcomes for specific ethnic groups’ (Commission on Race and Ethnic Disparities, 2021)’.
It’s not helpful to group people into lumps; it’s not helpful to cateorgise people as ‘non-white’ as by definition, the standard against to be measured would be white ethnicity, suggesting people with white ethnicity is normative, and anything else non-normative.
Returning to the Americas
I grew up in northern Alberta, Canada, mostly in Treaty 8 which you can see from the First People’s Map of Alberta.
Here are a few Native American tribes that lived in the province:
‘The original inhabitants of the area that is now Alberta included:
The Blackfoot Nation (Siksika, Piikani and Kainai)
The Chipewyan Nation (Dene Suline)
The Cree Nation
The Ojibwe Nation (Anishinaabe)
The Sarcee Nation (Tsuu T’ina)
The Stoney Nation (Nakoda/Assiniboine)‘
I’m not really sure how they capture this specific data, in the Canadian census, which asks, ‘are Indigenous people living on the reserves’ and ‘are Indigenous people living off the reserve.’ This doesn’t seem to capture rich data for the census, but the more specific data around the Treatys mentioned above is available here: Native Languages of the Americas website © 1998-2021. [http://www.native-languages.org/alberta.htm]
Peters and Mika (2017) provide a good sketch of the complexities using language for the people who originally lived in Canada, remarking that,
‘there has been opposition by various tribal groups and ‘first nations’ peoples to the terms ‘Indigenous’ and ‘Aborigine’ (and its cognates), although governments around the world continue to use both terms. Increasingly, the favoured term is ‘First Nations’ although this term is increasingly used in legal discourse especially in Canada to refer to members of legally recognized reserve communities’.
As it goes, my First Nations friends from Alberta prefer to be called ‘Indian’. I think we need to listen carefully to what terms individuals identify with, alongside groups. Exploring the Peters and Mika (2017) really brings to life the complexities of people’s identities, from the histories they inherit and the present world they live in.
To conclude, Data Day made me curious about demographic labels used in research and by governments, and after looking at some of these sources here in this blog, I recognise how sensitive people feel about the language used to describe them.
References
Alberta School’s Council Association (2019) First People’s Map of Alberta. Available at: https://www.albertaschoolcouncils.ca/about/indigenous-awareness/first-peoples-in-alberta [Accessed 21.02.22]
Commission on Race and Disparties (2021) Independent Report Summary of Recommendations. Available at: https://www.gov.uk/government/publications/the-report-of-the-commission-on-race-and-ethnic-disparities/summary-of-recommendations [Accessed 21.02.22]
Dyer, J., (2010) Hermeneutics, in International Encyclopedia of Education (Third Edition), 2010
Herrera, R. (1992). The Understanding of Ideological Labels by Political Elites: A Research Note. In The Western Political QuarterlyVol. 45, No. 4 (Dec., 1992), pp. 1021-1035 (15 pages) Published By: University of Utah.
Hughes, J., Camden, A.,Yangchen, T. (2016) ‘Rethinking and Updating Demographic Questions:
Guidance to Improve Descriptions of Research Samples’
Agnes Scott College. Available at: https://cdn.ymaws.com/www.psichi.org/resource/resmgr/journal_2016/21_3Fall16JN-Hughes.pdf [accessed 20.02.2022]
MARKS, R., CHIEF, RACIAL STATISTICS BRANCH, POPULATION DIVISION AND MERARYS RIOS-VARGAS, CHIEF, ETHNICITY AND ANCESTRY BRANCH, POPULATION DIVISION (2021) Improvements to the 2020 Census Race and Hispanic Origin Question Designs, Data Processing, and Coding Procedures. Available at:
https://www.census.gov/newsroom/blogs/random-samplings/2021/08/improvements-to-2020-census-race-hispanic-origin-question-designs.html [accessed 20.02.22]
Michael A. Peters & Carl T. Mika (2017) Aborigine, Indian, indigenous or first nations?, Educational Philosophy and Theory, 49:13, 1229-1234
Vaditya, J., (2018) Social Domination and Epistemic Marginalisation: towards Methodology of the Oppressed Article in Social Epistemology · May 2018