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Population and the Environment: Analytical Demography and Applied Population Ethics/UsamaBilal

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Revision as of 23:05, October 16, 2018 by UsamaBilal (talk | contribs) (Created page with "{{Attendee note |Post-meeting summary='''Most useful thing I've learned''': The idea of outlining several causal models and the predictions that they can make about a certain...")

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Notes by user Usama Bilal (Drexel Univ.) for Population and the Environment: Analytical Demography and Applied Population Ethics

Post-meeting Reflection

1+ paragraphs on any combination of the following:

  • Presentation highlights
  • Open questions that came up
  • How your perspective changed
  • Impact on your own work
  • e.g. the discussion on [A] that we are having reminds me of [B] conference/[C] initiative/[D] funding call-for-proposal/[E] research group

Most useful thing I've learned: The idea of outlining several causal models and the predictions that they can make about a certain phenomenon of interest, to then test which one fits the data better. This type of deductive reasoning is, I'd say, underused in my field. I'd like to think again about the causal models for fertility and to review potential causal models for epidemiologic transitions. However, at the same time, the conclusion from the lecture (and the paper) on these causal models for fertility ended up being about the importance of considering all models simultaneously, or, even better, considering how they have a differential effect over time. That is, some of the models may have an importance in the beginning of the fertility decline while some others may be more important in the later stages. I think we need to leverage the idea of feedback loops and endogeneity in complex systems to better accommodate the presence of multiple causal models. 

Planning to use knowledge: I plan to use the framework on migration determinants, especially at the macro level, and to leverage some of the data sources that were mentioned in the migration lecture. In particular, I'd like to see the connections between internal migration (rural to urban) in the determination of urban health outcomes. I'd also like to incorporate some of the lessons about causal models, but applying them to epidemioloic transitions.

Interesting conversation:

  • On the necessity to consider endogeneity in the causes of population dynamics. X affects Y than in turn affects X again.
  • On the necessity to consider inequalities and distributional effects

Reference material notes

Some examples:

  • Here is [A] database on [B] that I pull data from to do [C] analysis that might be of interest to this group (insert link).
  • Here is a free tool for calculating [ABC] (insert link)
  • This painting/sculpture/forms of artwork is emblematic to our discussion on [X]!
  • Schwartz et al. 2017 offers a review on [ABC] migration as relate to climatic factors (add the reference as well).

Epidemiological Transitions: https://www.jstor.org/stable/3349375?seq=1#metadata_info_tab_contents

Reference Materials

Title Author name Source name Year Citation count From Scopus. Refreshed every 5 days. Page views Related file
The epidemiologic transition: A theory of the epidemiology of population change Abdel R. Omran Milbank Quarterly 2005 413 13