Charles W. Cushman Photograph Collection: Grant Proposal
Bibliographic record
Abstract
Cushman observed American life with a keen eye and captured it with startling immediacy in Kodachrome.His work is skillfully composed and socially revealing.Indeed, much of Cushman's subject matter parallels that documented by the Farm Security Administration (FSA), which is now famous for its images of Depression-era farm families.Mr. Cushman's interest in poverty, industry, urban life and other facets of the American social and economic landscape is evidenced throughout his work: his photographs demonstrate a sustained interest in themes traditionally associated with the FSA and other social documentary photography.And, because Mr. Cushman was a pioneer in the use of Kodachrome (beginning to use the film only two years after it was introduced to the market in 1936), Indiana University's Cushman Collection is probably the most extensive color record of civilian life during the years of World War II.Mr. Cushman bequeathed his vast collection to Indiana University in 1972.The slides, neatly packed and labeled, remained in the suitcases in which they were delivered until a university archivist discovered them in late 1999.Although Mr. Cushman's earliest work is black and white, the Indiana University digital project will focus on the color slides.Digitizing them and presenting them on the World Wide Web will make these valuable images available to a national audience of social historians, documentarians, historic preservationists, and the general public.To provide access to the collection, Indiana University Digital Library team will create a relational database that will be used to generate an (EAD) finding aid, permitting users to search the collection by location, date, and keywords within the captions that Mr. Cushman wrote for each photograph.The finding aid for the Cushman collection will be enhanced with the addition of subject terms from the Library of Congress's Thesaurus for Graphic Materials.Our goal is to streamline the workflow for creating the EAD finding aid by using a database for entry of the various sources of data which will eventually go into the finding aid.We will make this database model available to other institutions to adapt to their own EAD applications.Indiana University has substantial experience in digitization, having received a National Leadership Grant in 1998 to digitize the university's multimedia materials pertaining to master songwriter Hoagy Carmichael.The collection of Cushman photographs, however, provides a groundbreaking opportunity to research and pilot-test methods of color restoration and to build a database from scratch.Additionally, the sheer size, age, and quality of the collection offers an experienced digital library team the opportunity to advance the knowledge of preserving Kodachrome slides and to offer recommendations and standards for their digitization.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".