Bibliographic record
Abstract
Purpose The purpose of this paper is to discuss the current state of the “paperless office” and explore how likely it is that libraries will be administered by librarians in paperless offices in the near future. Design/methodology/approach This paper surveys the literature on forecasts for the paperless office to determine whether library operations and offices could be as paperless as some of their collections might be in the near future. Findings The paperless office was once seen as inevitable, but is looking less far less likely given how we access and organize documents, how we read and understand information, and how we analyze what we read online and in print. Nonetheless, certain routine library operations would lend themselves almost immediately to paperless storage and retrieval processes and systems. Research limitations/implications More research is required on records management systems in libraries with a view to establishing largely paperless operations in the future. Implications for future research involve the establishment of processes and the testing of systems which would most easily lend themselves to standard library operations. Practical implications Recent research on reading and cognitive function indicates that there are certain practical implications involved in doing away with paper entirely. Nonetheless, certain routine library functions could be made paperless operations once practical considerations such as the choice of systems, establishment of work flow, policies and processes have been realized. Originality/value The paper makes the case for more research and exploration of the viability of paperless or near‐paperless library operations.
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 | 0.013 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.019 | 0.024 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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".