The future of information history
Bibliographic record
Abstract
Abstract This panel discusses developments in the scholarship of information history and speculates on its future. Previously, history was a distinct mode of research and a specialty community within information science; it operated largely outside of the mainstream scholarship that was underway within the dominant empirical and rational paradigms. Today, more social and culturally‐oriented approaches have gained momentum across the discipline and these frameworks include an historical perspective as one dimension of their conceptual apparatus. As a result, an historical sensibility is now embedded more broadly across a larger swath of scholarship. This is an exciting and welcome development for champions of history–but it is also problematical. The new historical dimension to research is diffuse and its practitioners typically do not identify as historians. To illustrate the new ambiguous place: there is no obvious home for this historical panel in the track‐based program structure of the ASIS&T annual meeting. From a variety of angles, our panel traces the recent breakthrough and mainstreaming of history and aims to characterize its new face. The panel includes a classically trained historian, a theorist, and two scholars whose research features historical themes but is centered outside an historical specialty. A concluding discussion among panelists and the audience will be guided by a big question: What is the future of information history?
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 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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.020 | 0.028 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".