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If you have any trouble searching, please click on "Search Tips" listed under the search bar on this page or check out our How-To for more detailed information. If you are still having trouble finding what you're looking for, just send us an email. We'd love to help you create a strategy to explore your research topic.
We have strived to make the data of the Fashion Calendar Research Database as open and accessible as possible. However, due to technological limitations, there may be cases where access is slightly limited or you want to create a dataset that isn't possible with the available search tools. For instance, while you can download search and graph results as JSON and CSV (respectively), due to processing limitations, search downloads are limited to the first 10,000 results. In such cases, accessing the full dataset in our Github repository may be helpful. In any case, please don't hesitate to reach out by sending us an email. We'd love to help and are also interested to learn about your particular use case, which could help us improve the database.
Misattributions, Errors or Omissions
The use of AI and machine learning technologies have expanded the ways users can use and interact with the publications in the Ruth Finley Collection. The technologies are not perfect and as a result have not captured the entirety of the data within the publications. There are a minority of pages that are unreadable, contain irregular listings or contact information. The user should consider the inherent margins of error associated with digitization and should refer to the original source when applicable.
Identity attributions can bring up the challenges associated with the categorizations of individuals, however, taking an intersectional approach that expands knowledge about marginalized and minority groups helps the user understand the historical diversity of the fashion and creative industries of the twentieth and early twenty-first centuries. The project team has added identity attributions that have been researched in reliable primary and secondary sources, and apologize in advance for any misattributions, errors or omissions. Please contact the project team with any corrections or questions by sending us an email. Please excuse any computer generated or human omissions or errors.