The challenges and opportunities of an open future for small publishers
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
<p class="first" dir="auto" id="d1121544e101">Many small publishers, such as university presses, society publishers, and not-for-profit publishers, are taking steps to prepare their journals for the transition to open access. However, the path to open is not always clear and there is plenty of risk involved in the transition. This is particularly true for small-scale publishers with thin operating margins that stand to lose the most. Conversely, being unable to make a successful transition to open access is even more concerning as the scholarly publishing world shifts rapidly in this direction and those that fail to join the movement may be left behind. Canadian Science Publishing is an independent and not-for-profit scholarly publisher, and we are committed to transitioning our journals to open access. We are preparing for an open access and open science future by developing partnerships, implementing journal strategic plans, and rethinking our approach to scholarly publishing. We have been making progress towards our goals, but we have also encountered challenges and learned important lessons along the way. In the spirit of openness, we would like to be transparent about these challenges to help other small publishers learn from our experiences, both positive and negative. It is our hope that the presentation stimulates discussion and provides insight for small publishers that are pursuing an open future.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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