A Brief History of the Future of Academic Libraries: Predictions and Speculations from the Literature of the Profession, 1975 to 2000--part one, 1975 to 1989
Bibliographic record
Abstract
During the last quarter of the twentieth century, the literature of academic librarianship was replete with articles predicting, anticipating, speculating, or cautioning about future possibilities for the field. The seminal works of F. W. Lancaster, who was one of the early predictors and enthusiasts of "paperless information systems," are the key points of departure for this literature. This article (which covers the period of time from roughly 1975 to 1989), as well as its second part (1990 to 1999), employs a citation-tracking method for gathering and reviewing this literature. Each work discussed in this article cites either Lancaster's work, or another work that cites it, so that the resulting literature review has grown from a common source of thought. The aim is to provide an analytical overview on how academic librarians saw and attempted to shape the future of their field during a period of unprecedented change.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".