Last week the entire Delhi Voter Project team had a full day meeting with one of our PI's and two officials from SNS. An interesting tension was present between putting into place an experimental design most likely to allow for relatively clear channels of causal impact and/or yield statistically significant results and one most likely to be feasibly scalable.
One criticism sometimes raised against experimental field research such as ours is that while an intervention may reveal important relationships/mechanisms from an academic research perspective, the actual intensity of effort and resources expended over the course of the experiment is such that, even in the event of finding a beneficial impact, it is impractical to implement the program on a larger scale. The nature of some of the discussions during the meeting were heartening because, while academic concerns were dominant (and in all honesty are also my primary interest), practicality and relevance from a policy standpoint were certainly given consideration. We have another meeting next week with two of the PI's and the SNS officials, after which the structure of the RWA intervention should be finalized.
Long ago, during my first year as a research assistant at JPAL, a professor and I were discussing the involved, and not so rarely frustrating, process of data analysis used to take results from the field and produce meaningful academic work. As he put it, being involved in this allowed one to "see what went into making the sausage". After three years or so of being enmeshed in that very process, it's been really useful for me to engage with a different sort of charcuterie, bettering my understanding of what goes into running a field experiment and gathering the data which I had too much begun to take for granted.
I've been spending this week in Landour working remotely in the company of Nilesh and Alicia, two other members of my PhD cohort also involved in research in India over the summer. While sitting at my laptop crunching away at Stata, being enveloped in a cloud as it rolls up the hillside has become a routine experience. After the din and heat of Delhi, it's not been an unwelcome one.
One criticism sometimes raised against experimental field research such as ours is that while an intervention may reveal important relationships/mechanisms from an academic research perspective, the actual intensity of effort and resources expended over the course of the experiment is such that, even in the event of finding a beneficial impact, it is impractical to implement the program on a larger scale. The nature of some of the discussions during the meeting were heartening because, while academic concerns were dominant (and in all honesty are also my primary interest), practicality and relevance from a policy standpoint were certainly given consideration. We have another meeting next week with two of the PI's and the SNS officials, after which the structure of the RWA intervention should be finalized.
Long ago, during my first year as a research assistant at JPAL, a professor and I were discussing the involved, and not so rarely frustrating, process of data analysis used to take results from the field and produce meaningful academic work. As he put it, being involved in this allowed one to "see what went into making the sausage". After three years or so of being enmeshed in that very process, it's been really useful for me to engage with a different sort of charcuterie, bettering my understanding of what goes into running a field experiment and gathering the data which I had too much begun to take for granted.
I've been spending this week in Landour working remotely in the company of Nilesh and Alicia, two other members of my PhD cohort also involved in research in India over the summer. While sitting at my laptop crunching away at Stata, being enveloped in a cloud as it rolls up the hillside has become a routine experience. After the din and heat of Delhi, it's not been an unwelcome one.
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