Bibliographic record
Abstract
The goal of this paper is to document how labour is divided and compensated (both monetarily and non-monetarily) in Canadian non-commercial scholarly journals. This study informs future research on sustainability in non-commercial academic publishing. As labour is essential for the continued success of these journals, understanding the extent (i.e., how many positions, how many hours per position), scope (i.e., which tasks are undertaken and who is responsible for them), and cost (monetary or non-monetary) of this labour will be critical in ensuring the sustainability of non-commercial academic journals in Canada. To investigate current practices, the authors distributed a survey to 484 Canadian journals meeting the above inclusion criteria. The survey was composed of two sections: how labour is divided at a journal (i.e., how many positions are there, what are the responsibilities of these positions, and how many work hours per week are dedicated to these positions) and compensation (i.e., does the journal provide monetary or non-monetary compensation to members of its editorial team, which positions receive compensation, and what is the source of these funds). The authors received 119 responses, for a 25 percent response rate. Among the main findings are that the majority of respondents compensate at least one journal position and that the source of these funds comes primarily from sponsoring organizations (i.e., affiliated institutional/university departments and scholarly associations). Additional findings include that the top three most commonly compensated positions are copyeditor, editorial assistant, and managing editor. Compensated positions such as translator, graphic designer, and copyeditor are often contracted out. Task distribution amongst editorial team members varies; however, editors-in-chief and managing editors are responsible for the greatest variety of tasks. Editorial assistants and managing editors tend to work more hours than other positions. Additionally, journal production was related to editorial team size, with larger teams producing more volumes on average than smaller ones. Recurring themes in free-text comments were large workloads, lack of compensation, and lack of recognition. This paper provides empirical evidence of the extent and variation of labour and compensation in Canadian non-commercial scholarly publishing. It provides data on current non-commercial journal practices which will be of interest to library publishers, journal editors, and other stakeholders in Canadian scholarly publishing.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".