We Are All Digital Now: Digital Photography and the Reshaping of Historical Practice
Bibliographic record
Abstract
Visiting a reading room in the last five years is a very different experience than what it looked like even fifteen years ago: while a few researchers carefully read archival documents in situ, most are crouched over their archival documents with a smartphone or digital camera in hand, taking thousands of photos that will be analyzed upon return to their home institutions. With the advent of digital photography and less-restrictive archival policies on digital reproduction for personal use, historical research is now characterized by quick trips to gather thousands of photos. What does this mean for the research and writing of history, however? How do researchers create their corpuses and on what information? What work takes place before the archival visit, after the archival visit, and how can we better support this sort of work? Drawing on a 2019 survey of 253 historians employed at Canadian universities, this article argues that through specific reference to the use of digital archival photography, we can see the varied ways in which historical work is being adapted to these new and emerging technological circumstances.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".