Srini, I agree the 500 responses is overkill - 390 would've
done,statistically. But in our past surveys, we've found 6% to 7% of the
responses being "outliers" that we've had to discard. And this time being a
national effort, we wanted to overdo things, if need be, since re-doing a
constituency is not really an option.
The survey does attempt to get some sense of the respondent's
socio-economic background - age, education, rural/urban, roof-type, basic
assets, stove-type, etc. And we've debated various ways of asking
questions, trade-offs between questions that are easily understood and that
are comprehensively stated, the impact of translation into Hindi and other
languages, etc. We've also stayed away from "incidental" assessments of
things like leadership qualities; instead, we've added a direct option
about whether the PM Candidate is an issue the respondent uses in deciding
whom to vote for.
I want to point out that the intent of this survey is NOT to be a barometer
of how India will vote but to identify issues that people can verbalize
(and MPs can use) in relation to their constituencies. The impact of having
over 2.5 lakh people discussing these issues with their friends and family
will be significant, we believe, in people making an informed choice in
voting.
I'll post a link to the questionnaire later today.
Kishore.
-----------------------
www.dakshindia.org
On Mon, Feb 10, 2014 at 2:02 PM, Srinivasan Ramani
<srinivasan...@gmail.com>wrote:
> Some thoughts -
>
>
> * The survey of 2.5 lakh would certainly be exhaustive but I personally
> feel it could be over-done. Sampling can be somewhat lesser than that to
> yield more focussed results (for easier post-survey processing, I suppose).
>
> * But that said, the survey could seek to not to fully replicate efforts
> such as what the CSDS' Lokniti already does. One weakness I believe that
> the Lokniti surveys have is that while the questionnaires gauge background
> and attitude towards politics variables quite well, they don't necessarily
> capture reasons and expectations that much well.
>
> So, for e.g.,if the questionnaire and data can be more than just "what are
> the reasons you vote for a candidate" .. maybe, "why do you think your
> choice of party/candidate is better than the alternative".. "what schemes
> have you benefitted from during MP's tenure / or hope to benefit from"..
> Also, opinions such as "who do you think could be an ideal leader?" to
> reflect opinions on the kind of representatives they would like to have ...
> is another thing that would be helpful.
>
> * Beyond political opinion, better knowledge of class backgrounds will
> also be useful (in terms of profession, homes, access to facilities etc).
>
>
> On Mon, Feb 10, 2014 at 11:06 AM, Kishore (Narasimhan) Mandyam <
> kish...@dakshindia.org> wrote:
>
>> Daksh is currently conducting a Nationwide in-field survey about people's
>> perceptions about their MPs. We're talking to nearly 2.5 lakh (that's
>> 250,000!) people in nearly 10,000 locations, in over 500 MP constituencies.
>> The math works out to about 500 responses in each Constituency - stratified
>> and randomized enough to give an analyst a fairly clear picture of what
>> people are thinking. The data consists of 10 demographic details (gender,
>> rural/urban resident, religion, occupation, qualification, roof-type,
>> assets owned, etc.), four "political awareness" points ("Did you vote..?",
>> "What are the reasons you vote for a candidate?" and so on) and upto 30
>> issue-based Performance questions (bijli / sadak / paani kinds of things).
>> Respondents tell us how important they think a specific issue is (Low /
>> Medium / High) AND how well they think their MP has done in that specific
>> issue. We've done thins kind of thing for Karnataka MLAs before and one of
>> the more populist results was a series of MLA Scorecards that appeared
>> pre-election in Vijay Karnataka, Indian Express and Times of India in 2013.
>> With this much-wider survey, though, we're wondering about the various
>> other things we could do - from mapping people's perceptions about caste
>> and criminality to inferring rural and urban unemployment rates. But that's
>> probably the low-hanging fruit. How else could this data be used? Ideas
>> welcome!
>>
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