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Record W2278915927

Enhancing Access to Primary Sources through Cross-Disciplinary Collaboration and the Digital Humanities: The Stephen L. and Enid Stover Papers

2015· article· en· W2278915927 on OpenAlexaboutno aff
Robert Briwa, Cliff Hight

Bibliographic record

VenueNew Prairie Press (Kansas State University) · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsnot available
Fundersnot available
KeywordsDigital humanitiesCross disciplinaryDisciplineHumanitiesLibrary scienceSociologyWorld Wide WebArtComputer scienceData scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

Dr. Stephen L. Stover retired from Kansas State University’s Department of Geography in 1989. The Stephen L. and Enid Stover Papers, officially donated in 2014 to the Morse Department of Special Collections at Kansas State University Libraries, document the history of the Stover family. Included in these Papers is a series of 35-millimeter slides that document Stephen L. Stover’s travels domestically and internationally. Consisting of approximately 16,600 well-preserved slides, the series spans over 50 years (1956-2009). The series features a wide range of images, with particularly strong foci on the physical and cultural landscapes of New Zealand and Oceania during the late 1960s; Manhattan and the Flint Hills region of Kansas; the American West and Midwest (particularly Kansas and Wisconsin); Europe; agricultural landscapes; Canadian provinces Ontario and Manitoba during the 1960s; and the Stover family at school, at home, and at play.\nA cross-disciplinary and collaborative approach to the Stephen L. and Enid Stover Papers aims to make the collection available to researchers and the public using elements from the digital humanities. For the Stover slide series, the goal of Special Collections is to have a digital version for improved access and not for preservation initially. Inventorying, organizing, describing, and digitizing the slide series is a collaborative process between subject specialists in geography, family members, and the university archivist. The slide series showcases the way cross-disciplinary perspectives and contributions during the process of describing materials enhance public access to said materials. Additionally, the creation of digital versions of the slides provides a rich resource for further work by digital humanities scholars to apply these sources in new ways, making them more valuable as a data source for future research.\nThis paper is divided into three primary sections. The first section illustrates how the Stephen L. and Enid Stover Papers and the collaborative work being done on the slide series fit within the greater field of digital humanities. In doing so, we discuss our working definitions of digital humanities and cross-disciplinary collaboration. The second section discusses the specifics of the archival process. It examines the way that collaboration between the Stover family, the university archives in the Morse Department of Special Collections, and representatives of K-State academic departments improves understanding of the context of the slides, and how increased awareness of their context can facilitate their application in research. The third section illustrates potential cross-disciplinary uses of the Papers, with in-depth explorations on the ways that researchers within geography and anthropology might make use of the slide series. The third section closes with a final discussion of “downstream” uses. Future researchers’ differences in geography, distance in time, access to advances in technology, and experience of the ebbs and flows of generational knowledge means that their access to the Papers through the means digital humanities ensures that its research value will have a life far beyond the scope of current potential applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0130.008
Scholarly communication0.0310.021
Open science0.0020.023
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0320.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.251
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2015
Admission routes1
Has abstractyes

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