Author Addendum Conundrum: Reconciling Author Use of Addenda With Publisher Acceptance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this paper is simultaneously to investigate researcher use and awareness of author addenda (e.g., the Scholarly Publishing and Academic Resources Coalition [SPARC] author addendum) and publisher awareness and acceptance of the same. Researchers at U15 Group of Canadian Research Universities institutions were targeted, and a survey was sent to faculty, graduate, and postdoctoral associations to share with their members. Following a low response rate, the survey was sent to a listserv of copyright librarians in Canada with a message that encouraged them to share it with researchers at their institutions. Eighty-one researchers responded to the survey. Eighty-six percent of researchers (n = 70) indicated that they were unaware of author addenda. Researchers were asked to identify how often they negotiate their publishing agreements, and of those who answered the question, 84.2% (n = 64) responded that they never negotiate. Thirteen publishers or publishing organizations were contacted and asked if they would participate in phone interviews about copyright practices and author addenda. Two large multinational publishers agreed to participate. Both publishers indicated that very few authors attempt to negotiate their agreements and that of those who choose to negotiate, even fewer use addenda. Both indicated that they do not accept the SPARC author addendum. This study’s small sample sizes mean that more information needs to be collected before firm conclusions can be drawn. Based on the responses from the two large publishers, the best way to help Tri-Agency-funded researchers may be for libraries and the Tri-Agency to negotiate with publishers for funder-based exceptions.
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.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.060 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it