Open Access, Scholarly Communication, and Open Science in Psychology: An Overview for Researchers
Bibliographic record
Abstract
Scholarly communication, Open Access (OA), and open science practices in Psychology are rapidly evolving. However, most published works that focus on scholarly communication issues do not target the specific discipline, and instead take a more “one size fits all” approach. When it comes to scholarly communication, research practices and traditions vary greatly across and within disciplines. This monograph presents a current overview that aims to cover Open Access (OA) and some of the newer open science-related issues that are affecting Psychology. Issues covered include topics around OA of all types, as well as other important scholarly communication-related issues such as the emergence of preprint options, the evolution of new peer review models, citation metrics, persistent identifiers, coauthorship conventions, field-specific OA megajournals, and other “gold” OA psychology journal options, the challenges of interdisciplinarity, and how authors are availing themselves of green and gold OA strategies or using scholarly networking sites such as ResearchGate. Included are discussions of open science strategies in Psychology such as reproducibility, replication, and research data management. This overview will allow psychology researchers to get up to speed on these expansive topics. Further study into researcher behavior in terms of scholarly communication in Psychology would create more understanding of existing culture as well as provide researchers with a more effective roadmap to the current landscape. As no other single work is known to provide a current look at scholarly communication topics that is specifically focused on Psychology, this targeted overview aims to partially fill that niche.
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 | 0.156 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.025 | 0.181 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.298 | 0.051 |
| Open science | 0.093 | 0.078 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".