Postdata conception
The developed system is called "postdata", praising two most important aspects of the system's methodology - just mentioned the philosophical rethinking of data in a modern way, in the spirit of postmodernism; and the desire to reuse the already existing abundance of statistical data, the discovery of which required enormous time, money, non-renewable resources.
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- Written by Ekaterina Bebenina
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Postdata conception is not linear. Every new research can and sometimes even should be a basis for a new one. it spares a time and gaves new points of view. As an example. Research of correlation between quality of education (according to Index of education)
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In the postmodern era, when nothing is final and generally unchangeable and everything depends on context and purpose, the data can probably also become such postmodern data, postdata.
But are such epithets possible for data? Such an attitude is appropriate not to the numbers themselves, but to the methodology. That is why it is not only possible, but it is precisely this that allows many problems to be solved.
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There are 19,000 universities in the world, according to WHED estimates. 14,000 universities are open enough to send information about themselves to Unirank and are ready to invite foreign students. Naturally, there are practically no military academies, seminaries and other fairly closed institutions of higher education among them. There are probably almost no universities out there that don’t teach students as much as sell diplomas. The rest are presented and worth exploring from various points of view. About two thousand of them also enter famous global rankings.
Tens of thousands of data sets are collected around the world each year only within the framework of the UN statistical office. Some data has been collected continuously for more than 50 years, but is often not used for purposes other than one-off requests from politicians, sociologists, and statisticians.
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A comparison of own achievements with the achievements of other universities can show a lot.
Then comes the task of choosing a reference, and it doesn’t have to be at the top of the ranking at all.
Not every university has outstanding goals, ambitions, tasks. The world respectively does not need 19,000 research universities dedicated to the unique teaching of a few talented students. The world needs professionals from various industries with different specialties, different living and career goals.
The reference can be a university according to its size, located in a city or village, having the same form of ownership, located in any particular country or even a specific city. At the same time the benchmarks may be slightly or significantly more successful in a certain ranking. The comparison can take place with the average statistical data of the universities of city, country, some countries, continent or even world, defining general trends. This kind of comparison helps the university find out which formats are more common or effective in achieving certain goals.
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- Written by Ekaterina Bebenina
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Why don’t the others do the same if everything is obvious and correct enough?
- Time. Many studies testing the theory were needed to present a system that includes several levels, connections, and relationships quite simply. Many versions were tested that eventually evolved into a ranking approach, which was the topic of my doctoral dissertation.
- Technical difficulties.
- Different rankings use different policies on the names of universities, for universities from non-English speaking countries even the spelling of the word university differs.
- The names of the countries are also changing.
- Commercial agencies almost never publish data in a format that is suitable for later use.
- Borders of countries change, universities unite and separate.
3. Methodological difficulties. Many universities obviously do rankings analysis, looking for a way to earn a good ranking. But the system is visible only outside its own limits. It is possible to create a system of strategic analysis and planning based on statistical data only going beyond the goals and tasks of a particular educational institution, on the methodological level.