Problems and issues in the arrangement and description of photographs in libraries and archival repositories
Bibliographic record
Abstract
Until recent years, archivists have been reluctant to consider photographs as being archival in nature. The evidential value possessed by some photographs was ignored and archivists also failed to see where the informational value of a photographic image could be enhanced when viewed within the context in which it was created. Instead, archivists preferred to arrange and describe photographs as discrete items. For assistance in this endeavor, archivists turned to members of the library profession. Librarians, for their part, found that photographs were not amenable to standard bibliographic formats or classification schemes devised for printed monographs. The result was the creation by members of both the library and archival professions of numerous and often idiosyncratic methods for the physical and intellectual control of photographs. The volume of photographic images acquired by libraries and archival repositories now makes it virtually impossible to continue dealing with photographs as discrete items. The research needs and methodologies of users have also changed; photographs are increasingly being sought as historical documents in their own right and not just as illustrations to accompany the written word. In response to these two factors, librarians began organizing and describing photographs as "lots" and archivists moved slowly toward the arrangement and description of photographs as archival fonds. This evolution, far from complete with regard to photographs, resembles an earlier evolution affecting the arrangement and description of textual archives, particularly manuscripts. Today archivists in many Western countries are seeking to establish standard formats in the description of archival materials. This goal has become particularly urgent in the face of computer technology and the desire to form automated archival networks. It remains to be seen whether the final standards adopted in Canada, for instance, will encompass photographs or whether photographs will retain a "special" status. Without question, photographs have and will continue to present members of the library and archival professions with problems In arrangement and description. This is demonstrated in the body of this thesis through a survey of the professional literature and through field work undertaken in six libraries and archival repositories in the Vancouver area and in Victoria, British Columbia. However, the existence of problems should not mean that the approach to photographic archives should be any different, in essence, from the approach and principles applied to textual archives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.266 | 0.397 |
| Meta-epidemiology (narrow) | 0.001 | 0.005 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.022 | 0.037 |
| Science and technology studies | 0.016 | 0.039 |
| Scholarly communication | 0.034 | 0.042 |
| Open science | 0.018 | 0.017 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".