I teach college reading, and one concept I discuss with students is “metacognition.” Cognition means thinking, and metacognition means thinking about thinking. I want my students not only to read and comprehend, but to be AWARE of whether they’re comprehending WHILE they’re reading–aware when the text is clear and aware when things are confusing. This is metacognition.

So…meta ethnography would be studying or conducting an ethnography about the process of ethnography. Meta analysis would be analyzing how people analyze. And meta interpretation would be observing and interpreting how interpretaion is conducted.

Here’s the best dictionary defintion I could find for meta in the sense you’re asking about:

A prefix meaning one level of description higher. If X is some concept then meta-X is data about, or processes operating on, X.

For example, a metasyntax is syntax for specifying syntax; metalanguage is a language used to discuss language; meta-data is data about data; and meta-reasoning is reasoning about reasoning.

Meta-ethnography

Meta-analysis is used differently in different sciences. In the phsycial sciences, meta-analysis is typically used to combine partial results from one study with the partial results of another study. For example, a study may be done that has many dependent variables. One of those variables may be interesting to a researcher performing a meta-analysis. The researcher will take the results of each study and try to isolate the effects of the variable that they are interested in studying. This type of meta-analysis is typically done when it is not possible or feasible to create a single study to specifically test the variable in question. Meta-analysis in the physical sciences is typically accepted more easily because of it’s quantitative nature. In other words, if numbers can be used to provide a proof, it’s easier for most people to believe those proofs. Within social sciences (sociology, psychology, parapsychology, etc.), meta-analysis is typically used to combine the results of smaller experiments to provide a sample size that is large enough to eliminate statistical anomalies. Social science experiments typically do not include tens of thousands of trials done using the same protocol, and so, the studies must be combined to get a sample that is large enough to overcome normal statistical variations. There are also qualitative aspects to social science experiments that cannot easily be evaluated using numbers – hence the disparaging moniker, “soft-science”. One of the criticisms of this approach to analysis is related to the fact that different methods are used to gather the data, and so, the data cannot be combined and treated as a single group of data. This criticism would be valid if the data were being treated like it all came from a single study, but, in good meta-analysis, the data is rated before it is combined. That is, data that is more directly related to the research work will be “weighted” more heavily than data that was only peripherally obtained. This provides an even playing field for all of the information gathered before the data is combined. Another criticism is that only the most successful data is being reported, and failed trials are being left “in the file drawer”. Again, this can be accounted for statistically, and the meta-analysis can provide for this variable. In this forum, meta-analysis is criticized related to parapsychology, but the same arguments used here could just as easily be used in other social science experiments. The missing fact is that when meta-analysis is done correctly, the objections that I mentioned above can be overcome, and there is no reason to dismiss meta-analysis in any of the social sciences, including parapsychology. As experimental techniques advance, and as analysis techniques are refined, the evidence will become more clear, and the objections to the techniques that are used will diminish. Thanks for the question!