I have finally gathered a substantial number of responses to my survey questionnaire on job search and social media. The survey was aimed at 16-24 year olds living in Scotland who are currently looking for a job. It has taken me literally months get there, and there have been plenty of trials and tribulations that should make for a good blog post or two in the near future. Maybe somebody out there can learn from my experiences.
In the meantime though, here are a few things I need to think about as I proceed to quantitative data analysis:
1. What is the consequence of having a heterogeneous sample? One of my supervisors questioned me about this on numerous occasions when I was building the survey questionnaire. Had I considered the nature of the group I was sampling? Did I really want to include all 16-24 year old jobseekers?
Well, for me, the answer is still the same now as it was then (which I suppose is a good thing) – yes and no. Yes, because I want my research to tackle the concept of networking at a broader level, and to provide a platform of knowledge from which to probe the networking behaviours of specific categories of jobseekers. No, because it means having to analyse a complex and multi-layered sample.
Within the 16-24 age range, I have picked up responses from people with hugely varying education levels (No qualifications > PhD qualifications), employment statuses, and job search goals. The latter of these is quite significant – some people have multiple goals e.g. I would like a job in my field but am also willing to settle for any job that pays. Making sense of these nuances, and how they have impacted upon networking behaviours during job search, is likely to be time consuming.
2. How representative is my survey sample? It is almost certain that there will be some bias. However, with regard to the general population of young jobseekers in Scotland (or anywhere), I would argue that sampling bias is unavoidable. I will present my argument in a future blog post, because I think the topic merits some discussion in isolation.
There are a few basics to consider though, in terms of demographics. For example, is there a proportionate representation of unemployed respondents? What about people who consider themselves to have a disability, or who were born outside of Scotland – have they a representative voice? To answer these questions, I need to compare my figures with those in general population surveys.
3. What is the data telling me? I suppose this is the fundamental question that any researcher would have to consider this stage. Does my data help me to answer my research questions? What trends are emerging from the data? Do they require further attention in the final qualitative element of my field work? To a large extent, the quality of the data I have gathered will depend on the quality of the questions I have asked.