Collective Writing: The Continuous Struggle for Meaning-Making
Bibliographic record
Abstract
This paper is a summary of philosophy, theory, and practice arising from collective writing experiments conducted between 2016 and 2022 in the community associated with the Editors' Collective and more than 20 scholarly journals. The main body of the paper summarises the community's insights into the many faces of collective writing. Appendix 1 presents the workflow of the article's development. Appendix 2 lists approximately 100 collectively written scholarly articles published between 2016 and 2022. Collective writing is a continuous struggle for meaning-making, and our research insights merely represent one milestone in this struggle. Collective writing can be designed in many different ways, and our workflow merely shows one possible design that we found useful. There are many more collectively written scholarly articles than we could gather, and our reading list merely offers sources that the co-authors could think of. While our research insights and our attempts at synthesis are inevitably incomplete, 'Collective Writing: The Continuous Struggle for Meaning-Making' is a tiny theoretical steppingstone and a useful overview of sources for those interested in theory and practice of collective writing.
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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 | 0.079 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.017 | 0.051 |
| Scholarly communication | 0.028 | 0.027 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".