Loss of inequality with aggregate measure

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Rachel Gould

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Mar 23, 2022, 9:02:35 AMMar 23
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Hello all,

One of the greatest challenges of using an aggregate measure is the challenge of seeing at the level of the individual. There are certainly benefits and important functionalities to having an aggregate measure.

The loss of the recognition of the individual and the individual situation, however, I find disconcerting, if not downright troubling.

How then, when we are in need of using an aggregate measure, can we increase our sensitivity to the individual?

In terms of the case of YoGL, a person with a physical limitation in a wealthy country, or even a wealthy person in a poor country, will fare far better than a person with a physical limitation who does not have resources, either from the state or personally. A person living in an area more sensitive to climate change (e.g., New Orleans in the US) will fare far differently than a person living in an area less at risk of climate change. And those areas may be an entire country or just a region within a country. How do we account for all of this when we take an aggregate measure?

If we are going to be successful in finding a better assessment tool than GDP, which I think we all agree is important, then I think we have to expand our scope of consideration a bit farther. And yes, there is a challenge of not expanding the scope too far, as others have mentioned. There do have to be parameters so that it can be used effectively and understood easily.

This is a fascinating topic. Clearly it's got me thinking about it a great deal. I hope the same is true for others and I'd love to hear more.

Rachel

Dr. C M Lakshmana

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Mar 23, 2022, 9:48:35 AMMar 23
to PERNSeminars - List, Rachel Gould
It is absolutely right , I agree too.
With regards
C M Lakshmana


From: Rachel Gould <rache...@gmail.com>
Sent: Wednesday, March 23, 2022 2:57:06 PM
To: PERNSeminars - List <pernse...@ciesin.columbia.edu>
Subject: [PERN Cyberseminar] Loss of inequality with aggregate measure
 
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Tom Dietz

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Mar 23, 2022, 11:04:12 AMMar 23
to Rachel Gould, PERNSeminars - List
Rachel's points are important ones. In the environmental sociology literature I keep referring to, issues of inequality have been addressed in two ways.  Some studies focus on measures specific to groups.  Ideally one would do this taking account of intersectionality but data limitations in secondary data for nations, US states, etc. so far don't allow us to go very far in that direction.  So, for example, a number of studies have used gender (as a binary) specific life expectancy, but measures of environmental stress remain aggregated.  A  second approach is to consider inequality as a structural factor/ driver influencing overall well-being and/or stress on the environment--not surprisingly inequality reduces sustainability as it is operationalized in this work.  This lit is aware of the limits of these analyses but is trying to make some progress with the data available.

Some examples: 
Jorgenson, Andrew K. 2015. "Inequality and the Carbon Intensity of Human Well-Being." Journal of Environmental Studies and Sciences 5(3):277-82.
Jorgenson, Andrew K, Thomas Dietz and Orla Kelly. 2017. "Inequality, Gender and the Carbon Intensity of Human Well-Being in the United States." Sustainability Science. doi: https://doi.org/10.1007/s11625-017-0517-2.
Jorgenson, Andrew K, Thomas Dietz and Orla Kelly. 2018. "Inequality, Poverty, and the Carbon Intensity of Human Well-Being in the United States: A Sex-Specific Analysis." Sustainability Science 13(4):1167-74.
Kelly, Orla, Ryan P Thombs and Andrew Jorgenson. 2021. "The Unsustainable State: Greenhouse Gas Emissions, Inequality, and Human Well-Being in the United States, 1913 to 2017." Socius 7:23780231211020536.

That is one reason there is a parallel track using subjective well-being measures as that allows data at the individual level where differences across intersectional categories of gender/ethnicity/class/physical limits, etc. and refined measurement of those social groupings (e.g. moving past gender binaries) can be considered depending on what is collected and sample sizes.

Best
Tom

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-University Distinguished Professor of Environmental Science and Policy, Sociology and Animal Studies

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Michigan State University

-Gund Affiliate, Gund Institute for the Environment, University of Vermont

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Hultquist, Carolynne Grace

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Mar 23, 2022, 11:07:53 AMMar 23
to Dr. C M Lakshmana, PERNSeminars - List, Rachel Gould
Hello all,


The two primary things that I’ve taken issue with in the nature of measures are how they average out and thereby lose the extremes (unless a homogeneous unit, the measure isn’t realistic) and how you don’t know if its the same individuals having these compounded issues in indices. 

A step in that direction could be first calculating individual/household level measures (this requires the raw data really as it is lost later in aggregates). Many at CIESIN watched this talk by the US Census Bureau on Community Resilience Estimates with interest. This approach opens up options of multiple categories of risk factors at the household and individual level. There is a lot of methodological development that can be done in this space to produce data that is still privacy preserving, but is also more informative on vulnerability, exposure, and wellbeing for households/individuals.


Best,

Carolynne Hultquist, Ph.D.
Center for International Earth Science Information Network (CIESIN) and Lamont-Doherty Earth Observatory (LDEO),
The Columbia Climate School, Columbia University

Kathryn Grace

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Mar 23, 2022, 11:33:38 AMMar 23
to Hultquist, Carolynne Grace, Dr. C M Lakshmana, PERNSeminars - List, Rachel Gould
Thanks Carolynne and Rachel,
I also think that working at a finer scale (individual-, household-, community-level) facilitates engagement with climate change and environmental change data/measures in ways that reflect how people in a given place live and work and interact with their surroundings and each other.  This finer scale approaches also support efforts to incorporate gender-, class-, disability-, race-based inequalities (and others not listed) that often play out at the community scale.  

With the vast amounts of fine-scale georeferenced survey data, and the rapid growth of remotely sensed data, and computational capabilities, we have many opportunities to develop more place-based measures that reflect the lived experiences of marginalized groups.  This approach supports community/stakeholder engagement and also provides insight into how certain types of interventions and systems may actually work to exacerbate inequalities. 

Kathryn Grace



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Kathryn Grace
Associate Professor | Department of Geography, Environment, and Society
Associate Director | Minnesota Population Center
University of Minnesota, Twin Cities
pronouns: she (but I'm okay with they)

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Dr. C M Lakshmana

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Mar 23, 2022, 12:04:29 PMMar 23
to Hultquist, Carolynne Grace, PERNSeminars - List, Rachel Gould
Excellent 👍👍🙏

From: Hultquist, Carolynne Grace <cgh...@psu.edu>
Sent: Wednesday, March 23, 2022 8:37:48 PM
To: Dr. C M Lakshmana <laks...@isec.ac.in>
Cc: PERNSeminars - List <pernse...@ciesin.columbia.edu>; Rachel Gould <rache...@gmail.com>
Subject: Re: [PERN Cyberseminar] Loss of inequality with aggregate measure
 
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