Jstor dfr. JSTOR Home 2022-10-25

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JSTOR (short for Journal Storage) is a digital library and archive that provides access to thousands of academic journals, books, and primary sources. It was created in 1995 as a way to provide libraries with a reliable and efficient way to digitize and preserve their collections. Today, JSTOR is used by universities, research institutions, and other organizations around the world as a comprehensive resource for scholarship and research.

One of the key features of JSTOR is its use of the Data for Research (DFR) service, which allows researchers to access and analyze data from a wide range of sources. DFR is a powerful tool that enables scholars to undertake large-scale, data-driven research projects and to explore new research questions and directions.

One of the main benefits of DFR is its ability to provide researchers with access to a wide range of data sources, including digitized primary sources, such as manuscripts, photographs, and maps, as well as secondary sources, such as articles and books. This allows scholars to explore and analyze data from a variety of sources, providing a more comprehensive and nuanced understanding of their research topic.

Another advantage of DFR is its ability to facilitate collaboration among researchers. DFR provides tools for sharing data and for collaborating on research projects, allowing scholars to work together and share their findings with one another. This can lead to new insights and discoveries, as well as to the development of new research questions and directions.

Overall, JSTOR and DFR are important resources for scholars and researchers looking to access and analyze data from a wide range of sources. They provide a valuable tool for exploring new research questions and directions, and for collaborating with others in the field.

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jstor dfr

First, scholars have, for a considerable time, recognized national, confessional, and conceptual differences within the broad category of the Enlightenment. What format is the data? It was developed to deal with very large datasets which require an agreement, but can be used with smaller ones as well. Most of the time, the entries for page numbers are simply 42, or 61. This corresponds more or less to the pattern of usage for this expression across the whole JSTOR database see Fig. There could be a simple explanation: the article might start on page 42, and end on page 65, and there is furthermore an erratum on page 362. But this singular view has been challenged, first and foremost by scholars who wished to introduce national, confessional, or regional differences.

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Known Quirks of JSTOR/DfR Data

jstor dfr

It could well be that these kinds of questions are less likely to appeal to nonspecialists, who may not always see the point or what is at stake in such arguments. This is as expected, and could be parsed as integers. The following list is thus inevitably incomplete. Furthermore, the pages need to be parsed properly: you will run into troubles if you calculate page numbers like 75284 - 42 + 1, in case the number was parsed badly. Could this be an instance of one term simply being replaced by another? The two best clues for assessing this question are disciplines and journals.

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JSTOR Home

jstor dfr

Data is available in either XML or CSV. The primary indicators I use to gauge such adoption are keywords: I start by looking at how the different qualifiers of the Enlightenment have been used over time, by discipline, and in conjunction with other terms such as place-names. The place of these theorists is remarkable not only in itself but also in contrast with that of earlier Enlightenment scholars. At the same time, a few national Enlightenments do also receive considerable attention, and have done for quite some time well before 1981 in any case: see Fig. If you have a concern that your copyrighted material is posted here without your permission, please contact us and we will work with you to resolve your concern.

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Read Data from JSTOR/DfR • jstor

jstor dfr

In most cases, the error will go away. I am also especially grateful to James Schmidt, for his detailed and extremely helpful feedback on a first draft of this essay. There are many other problems or peculiarities like this. Indeed, the strong showing of these particular Enlightenments tells us, more than anything, that this method of mining the JSTOR data returns plausible results. There are also less lofty reasons. If your search is beyond 1,000 items then the data set will be a random sample of all items in the search.

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Known Quirks of JSTOR/DfR Data • jstor

jstor dfr

The Case of the English Enlightenment Why does interest in some national Enlightenments take off and not in others? Important: you can only download up to 1,000 items in a single request. All data sets come with citations by default. But when we compare more closely related patterns of usage, a narrative may start to emerge. These numbers are meant to supply only a very general idea about the level of interest that scholars writing about the Enlightenment might have taken in these different national versions. There are multiple possible explanations, which the graphs alone are ill-suited to disentangle. Conclusion This experiment in data mining leaves one with an overriding sense that many debates about the Enlightenment take place in isolated corners of academia.

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Enlightenment Scholarship by the Numbers: childhealthpolicy.vumc.org, Dirty Quantification, and the Future of the Lit Review

jstor dfr

Indeed, if we were to include scholarship written in other languages, the standing of the Scottish Enlightenment would likely decline slightly. The danger that lurks in these terminological woods, however, is the temptation to read too much into a label. Because DfR counts documents, this means that any trends in the data must take into account variations in the size of the total holdings. . Then there is a third kind of scholarship, one that focuses more on defining terms. The metrics one can produce using DfR thus vary significantly from other types of data-mining results. The overall number of history documents also dropped significantly, from 1,820 to 1,502 i.

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Introduction to Using JSTOR Data for Research

jstor dfr

At the bottom of the Charts View screen is an option to Download data for year chart. This is as expected, and could be parsed as integers. The question is, are we always assessing the right works? You can convert XML to CSV by using Examples of data sets for research JSTOR DfR datasets lend themselves to visualization with a variety of tools. The question then becomes one of knowing whether there are any common features that could explain the success or, conversely, the failure of certain kinds of scholarship. Indeed, it would be more likely for interest in specific, separate Enlightenments to exhibit a different pattern of usage since this would indicate that a smaller field of scholars, probably under a common methodological thrust, had adopted a concept.

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jstor dfr

But the data themselves are often quite messy. But they are all well represented in JSTOR, making data mining one of few options for studying Enlightenment scholarship across multiple disciplines. The More Info link under each citation displays the top N-grams for each article. Unfortunately, sometimes the page is specified like this: v75i2p84. Simply looking at these figures, can we venture any hypotheses about how scholars thought about the Enlightenment? This is also what quantitative analysis is best suited to deliver. Now, I am not suggesting that thoughtful analysis and engagement with individual works can be replaced with number crunching. On Google Books, I found instances from the 1850s.

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