Coalition Publica: Collaborating for Equitable Open Access
Bibliographic record
Abstract
Érudit and the Public Knowledge Project (PKP), together as Coalition Publica, have been collaborating on supporting the transition to sustainable open access publishing in the Social Sciences and Humanities in Canada by building a non-commercial, open source national infrastructure for digital scholarly publishing, dissemination, and research. Working in a bilingual national context across teams that span the globe and produce open source software used by over 34,000 journals worldwide, means that at its foundation Coalition Publica has a vested interest in supporting and sustaining a multilingual and bibliodiverse research literature that responds to community needs. Along with a presentation of the Coalition Publica project, this talk will highlight efforts by the Érudit and PKP teams to foster collaborative approaches to achieve common goals of equitable participation in knowledge creation for the public good. This presentation will highlight initiatives include a new in-kind, fee-free route toward PKP Membership through the Community Contributor Pathway, and updates to the Membership fee structure that enable communities in Low, Lower Middle and Middle Income Countries to be better integrated with the project’s governance. We will also highlight resources and interest groups that foster multilingual development of PKP software and documentation. Finally, we’ll cover how Érudit works with library partners to increase multilingual and French content in the DOAJ and advance the Partnership for Open Access that allows libraries to contribute financially to support the notably independent and non-commercial journals that participate in Coalition Publica. As a national effort that brings together scholarly journal publishers, university research libraries, and researchers in the social sciences and humanities, Coalition Publica is providing a way for stakeholders in Canada to collaborate to ensure community-driven scholarship thrives in a sustainable open access 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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.074 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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; 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".