Let's see how subject tagging plays out in another core demography database from our applied demography guide, PubMed, published by the National Library of Medicine. Before we begin, I would encourage you to create an account in this database by simply clicking on Sign into NCBI. This will allow you to save search strategies, as well as create ongoing alerts.
If you look at the pull down menu, you'll see that there are a number of government databases that you're being able to search in this interface. We're simply going to focus on PubMed, which is a subject library database for biomedical scholarly literature and also MeSH, which stands for Medical Subject headings, which is essentially the thesaurus used by the National Library Medicine indexers. Let's go ahead and do a search anywhere for immigration and living arrangements in PubMed.
Unlike sociological abstracts, this interface does not provide you with a list of all the subject tags used to describe all the records. However, PubMed provides you with a nifty tool for identifying relevant MeSH headings used from your initial search. To see these, you simply need to click on See More, under the search details. And you can see how it's translating immigration and living arrangements using different MeSH headings.
The ones that we're going to pull out from our search here are immigration and emigration for the term immigration. And for living arrangements, we're going to use this term resident characteristics. Let's see what these look like using the MeSH tags. To do this, you select MeSH. And we're going to go ahead and search for immigration. And we'll look at resident characteristics in a second.
As you can see, the MeSH the source is much more comprehensive, providing you with subheadings and some other terms that people use for index terms in their articles to describe their research. You may want to explore some of these terms to be able to make future searches more effective. But you can also notice, if you scroll down, that there's a hierarchy that MeSH indexers use to categorize these particular articles.
So you can see emigration has a much broader term, human migration, population dynamics. If we select population dynamics, it will pull up that particular term. And here you should see demography population dynamics and human migration and immigration as narrower terms. Let's go ahead and keep it at a broad subject area. And let's go ahead and select statistics and numeric data as a subheading. And we're going to add that to our search builder
Let's go ahead and search for the term resident characteristics. It also has a description, as well as subheadings, other terms that people have used, and it provides you with broader and narrower terms. What we need to do is, we need to decide how we want to add this particular turn to our search strategy. So we have a decision whether or not we want to combine it with and, or, or not. What we want is, we want records that are tagged with population dynamics and resident characteristics.
This will provide us with a much narrower, more focused search, or would basically give us articles that have either one of these tags on it and not, of course, articles without either one of those tags. Let's select and add that to our search builder, and go ahead and search PubMed. Since this is a biomedical database, we may want to filter our research to only records that are about human beings.
If we select, under species, humans, it was selected before, this will eliminate any articles about non-human research. If you select a particular article that seems relevant to you, you can explore the MeSH terms that are used to describe those. And, again, you can build and write down those terms to help you look at future research terms that you might want to use for future searches. It's fairly easy to create an alert. Once you have created that search strategy, you can save that search and then simply add it to an alert.