Confused about copyright? Assessing Researchers’ Comprehension of Copyright Transfer Agreements
Bibliographic record
Abstract
INTRODUCTION Academic authors’ confusion about copyright and publisher policy is often cited as a challenge to their effective sharing of their own published research, from having a chilling effect on selfarchiving in institutional and subject repositories, to leading to the posting of versions of articles on social networking sites in contravention of publisher policy and beyond. This study seeks to determine the extent to which authors understand the terms of these policies as expressed in publishers’ copyright transfer agreements (CTAs), taking into account such factors as the authors’ disciplines and publishing experience, as well as the wording and structure of these agreements. METHODS We distributed an online survey experiment to corresponding authors of academic research articles indexed in the Scopus database. Participants were randomly assigned to read one of two copyright transfer agreements and were subsequently asked to answer a series of questions about these agreements to determine their level of comprehension. The survey was sent to 3,154 participants, with 122 responding, representing a 4% response rate. Basic demographic information as well as information about participants’ previous publishing experience was also collected. We analyzed the survey data using Ordinary Least Squared (OLS) regressions and probit regressions. RESULTS AND DISCUSSION Participants demonstrated a low rate of understanding of the terms of the CTAs they were asked to read. Participants averaged a score of 33% on the survey, indicating a low comprehension level of author rights. This figure did not vary significantly, regardless of the respondents’ discipline, time in academia, level of experience with publishing, or whether or not they had published previously with the publisher whose CTA they were administered. Results also indicated that participants did equally poorly on the survey regardless of which of the two CTAs they received. However, academic authors do appear to have a greater chance of understanding a CTA when a specific activity is explicitly outlined in the text of the agreement.
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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 | 0.051 | 0.270 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".