Bibliographic record
Abstract
Dominant initiatives focusing on research integrity are changing the research landscape by leading to the development and application of rules, guidelines and standards that researchers across borders have to abide by. There is an increasing attention within these initiatives to the importance of research fairness for conducting responsible research. However, some stakeholders view research fairness as separate and sometimes even conflicting with research integrity. To make sense of these accounts, I explore the relationship between research integrity and research fairness. I argue that dominant research integrity initiatives are currently at odds with research fairness. This is because these initiatives largely ignore anticolonial views about research and thereby perpetuate coloniality in research. Furthermore, dominant initiatives only engage superficially with aspects of fairness that are least controversial and current. Moreover, these research integrity initiatives impose Eurocentric ideals about responsible research to other countries, thereby contributing to “ethical imperialism”. Considering the wide reach of dominant research integrity initiatives and their influence on research, it is therefore urgent to develop an anticolonial research integrity agenda that takes fairness seriously.
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 | MetaresearchResearch integrity Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | MetaresearchResearch integrity Domain: Methods · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | high |
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 | 0.337 | 0.344 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.016 | 0.162 |
| Scholarly communication | 0.037 | 0.036 |
| Open science | 0.005 | 0.034 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".