Bibliographic record
Abstract
This paper examines how the use of and preference for the English language in scholarly communication enacts epistemic oppressions on global, regional, and local stages to delegitimize knowledge and knowers active in other languages and epistemological frameworks. Specifically, this paper argues that internationalized languages of economic and metrics-based value interact and intersect with the over-valuation of English, which has detrimental consequences. Four readings of the interplays between language and value in the scholarly ecosystem are presented. As questions of knowledge production, epistemic oppression, and justice are not confined to one discipline or community, each reading engages with the theory and praxis of scholars from local and Indigenous communities, and scholars and practitioners in a range of other areas. The first reading, Language Has Value, examines the knowledge and value embedded in languages, as well as the implications of monolingualism for global knowledge production and use. Focusing on the publishing industry, Language of Value interrogates the internationalized economic values that shape mainstream approaches to open access and overlook regional situations. Language of Evaluation attends to the symbolic market of research metrics and evaluation criteria that forces researchers to choose between topics that are locally relevant and those deemed important by the mainstream community. These readings are followed, in Language and Value, by lessons learned from established models and tools for knowledge production and dissemination that actively resist intersecting oppressions. The paper closes with a call to the research community to imagine and work for sustainable and equitable approaches to scholarly communication that break open and away from the epistemic enclosures dominating the present system.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Scholarly communication Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | medium |
| gpt | Scholarly communication Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".