- 7/8/2015 7:57:02 AM
@kq4ym. Right, everyone has ideas and theories that they would like to explore. Those who have grant money get to do that exploration, often in what we later see can be somewhat frivolous adventures.
- by kq4ym, Data Doctor
- 7/7/2015 7:10:12 PM
I too wonder about lots of those studies maybe being done "because grant money is available." In our never ending search for the truth sometime we seem to go a bit out of the way looking for answers in unusual places especially if someone else pays for the search.
- by SaneIT, Data Doctor
- 6/10/2015 8:03:46 AM
I'm not arguing here but I really don't think that we are lacking a cure for cancer due to the fear of lost consumers. We do have answers for many types of cancer and the pharmaceutical companies still make money on those drugs. I'm not sure if you know anyone who has had cancer but I know a half dozen and cancer is just one of the ailment that they suffer. There is plenty of room to make money producing drugs. I think our biggest problem is time and money. The forms of cancer that take people quickly are seen less frequently and they are often caught late so finding if a drug actually works is very tough. Then we get back to the research issue, there isn't money to look at every form of cancer so we get a best effort on a handful of cancers that researchers are interested in. I don't think this will change any time soon.
- by Phoenix, Data Doctor
- 6/10/2015 1:09:23 AM
@ SanelT Sadly you are right. Although there is a lot of interest right now in using analytics for healthcare it is very doubtful that they will receive enough research funding for preventive healthcare. Big pharmaceuticals who are the main healthcare funding agencies other than the government will not be interested in funding something that could mean a potential loss of consumers for their products.
- by Phoenix, Data Doctor
- 6/10/2015 1:04:54 AM
@ Jim That is a very good way of using the data. It will make a huge difference to the lives of many people affected by this. They could also create a potential skill analysis and skill matching data base to help people who loose their to find new jobs. I think this data is already available through employment job banks but specific skill set matching can be done more effectively through analytics. It could also provide information about the skills in demand and how to upgrade skill sets to match changing needs of the work environment.
- by SaneIT, Data Doctor
- 6/9/2015 8:00:05 AM
@Phoenix I agree that sometimes those resources are better spent elsewhere but that can be difficult to nail down and in many cases they are collecting data on the easiest target. First we have to look at who is collecting the data, if it's a government entity responsible for employment statistics then they won't be trying to cure cancer ever and no matter how efficient they get I wouldn't expect that any budget savings from their department are going to be shifted to cancer research. I think we need to look at how they can do their part better and what data most effectively tells the story that they need to tell.
- 6/8/2015 1:27:31 PM
@Ann. You're right about the publish or perish rules and the copycat mindset. I guess I'm kind of a traditionalist in thinking that there needs to be more of a balance between research largely for publication and the original purpose of education, teaching.
- by RbtKlein, Prospector
- 6/8/2015 1:21:40 PM
You've summed everything up very nicely here. The meta nature of the story, the motivation of the authors, and the positive results to be gained from these hybrids of journalism and mere content creation.
- by AnnFeeney, Statistician
- 6/8/2015 1:05:50 PM
Another possible factor is that "big data" and "predictive analytics" are still buzzwords that can draw journalist and public attention to a story. People who wouldn't cover or read a story about the number of new applications for unemployment might cover or read a story about how big data and predictive analytics can measure unemployment data.
We also have the publish or perish model for academics, which can encourage redundant studies, if only because the first study found positive results. While another analysis of the same kind of problem won't necessarily advance knowledge, it can advance a career, while a more groundbreaking study with null results is far less likely to get published, no matter how important it might be for the research community to know about the results.
Then there are the studies that are the redundant or obvious bases for further studies. For example, now that we know that phone calls can provide near-real time data about layoffs, that might be a base for questions such as whether growth in calls to recruiters, resume services, etc.. can provide an earlier indication of layoffs.
- 6/8/2015 9:14:11 AM
@Phoenix. Good point about how the money on that research project could have been better spent. For example, rather than identify the layoff that everyone already knew happened, maybe use data to identify new employers who might want to move into that same area.