I have two comments with respect to what you wrote:
FWIW I'm an undergrad who is currently writing his thesis (empirical economics). I use the German Socio Economic Panel data set, which is a representative survey of ~11,000 German households (totaling about 79,000 individuals over 28 years). The reason why I picked a data set instead of collecting my own data is precisely to avoid the situation of the social sciences student you describe. As an undergrad, getting data is extremely difficult. You usually get about 6 weeks to write your thesis and you have absolutely no training in data collection and/or survey design. Getting data from students is your best bet, but nobody wants to answer your questionnaire because…hold your breath…everyone is sending out questionnaires. I get spammed with these things. Luckily, nobody has asked me to pretend that I am a 13 year old. So quite frankly most students panic after about 2-3 weeks and they will try to do anything to get out the situation. The alternative is not graduating and paying tuition for another year.
Secondly: Undergrad thesis =\= scientific paper. The fraction of undergrads who end up being social scientists is…tiny. Out of 300-400 econ students who graduate at my uni every year, I think 20 or less will go onto grad school (I'm proxying the number by thinking about how many went to do an MPhil). Now econ grad school is a different beast. Essentially you either end up doing experimental research or you work with observational data (assuming you are not a theoretician, those exist too; Economics is pretty much applied mathematics at that level.). Experiments can be checked and working with observational data requires a trove of econometrics. Trying to fool a panel of econometricians isn't easy, especially when these days you have to send in your data to the journal (or so my supervisor says; he has a paper forthcoming in the Quarterly Journal of Economics).
Social science in general is becoming more and more computational and statistically rigorous. Gone are the days when an "expert" would find a correlation between two variables and then speculate which way the causality flows…if any.
FWIW I'm an undergrad who is currently writing his thesis (empirical economics). I use the German Socio Economic Panel data set, which is a representative survey of ~11,000 German households (totaling about 79,000 individuals over 28 years). The reason why I picked a data set instead of collecting my own data is precisely to avoid the situation of the social sciences student you describe. As an undergrad, getting data is extremely difficult. You usually get about 6 weeks to write your thesis and you have absolutely no training in data collection and/or survey design. Getting data from students is your best bet, but nobody wants to answer your questionnaire because…hold your breath…everyone is sending out questionnaires. I get spammed with these things. Luckily, nobody has asked me to pretend that I am a 13 year old. So quite frankly most students panic after about 2-3 weeks and they will try to do anything to get out the situation. The alternative is not graduating and paying tuition for another year.
Secondly: Undergrad thesis =\= scientific paper. The fraction of undergrads who end up being social scientists is…tiny. Out of 300-400 econ students who graduate at my uni every year, I think 20 or less will go onto grad school (I'm proxying the number by thinking about how many went to do an MPhil). Now econ grad school is a different beast. Essentially you either end up doing experimental research or you work with observational data (assuming you are not a theoretician, those exist too; Economics is pretty much applied mathematics at that level.). Experiments can be checked and working with observational data requires a trove of econometrics. Trying to fool a panel of econometricians isn't easy, especially when these days you have to send in your data to the journal (or so my supervisor says; he has a paper forthcoming in the Quarterly Journal of Economics).
Social science in general is becoming more and more computational and statistically rigorous. Gone are the days when an "expert" would find a correlation between two variables and then speculate which way the causality flows…if any.