An interactive reading environment for online scholarly journals
Bibliographic record
Abstract
Purpose The purpose of this paper is to provide an overview of a set of reader‐oriented tools developed as part of an open source journal production and access system. Design/methodology/approach The paper outlines key elements of the reading tools component of Open Journal Systems (OJS). A design rationale is provided, and related to the key elements of the system. The philosophy behind the development of the reading tools is described, and relevant published research in support of the design is presented. Findings OJS ( http://pkp.sfu.ca/ojs ) is a web‐based, open source editing, management, and production application designed for publication of scholarly journals online. The reading tools developed for OJS are a useful addition to the feature set of OJS, providing journal readers with a richer reading environment, promote active reading, and increase the level of critical engagement with journal article content. Practical implications Readers may find that the tools described, as well as the larger system of which they are a part, could be usefully adopted in their own institutional context. Originality/value This paper provides an introduction to the design philosophy behind a reader‐oriented set of tools that will be of interest to those engaged in online reading research, and information interaction design. It will also be of value to those interested in open access, as well as those interested in open source software development.
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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
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".