Fostering open science and responsible research practices: A pre-post study
Bibliographic record
Abstract
Background Educational initiatives could foster the adoption of open science (OS) and responsible research practices (RRPs). This single group pre-post study evaluated the impact of an educational intervention on increasing the adherence, knowledge and perceptions about adopting OS practices and RRPs among graduate researchers at a Brazilian University. Methods Graduate students from a southern Brazilian university were invited to participate in a course addressing OS and RRPs. The intervention was an online interactive course on OS and RRPs. The number of OS outputs, including Open Science Framework (OSF) accounts, study registrations, protocols, analysis plans, data sets, preprints, and the number of projects published by each participant were collected before and after the intervention. Additionally, a self-administered online questionnaire was applied before and after the intervention to evaluate participants’ perceptions on RRPs, OS practices and on the current researchers’ evaluation system. Results Eighty-four students finished the course and 80 agreed to participate in the study. The number of OSF accounts increased from 7 to 78 after the course, and the number of projects increased from 7 to 10, six months after the intervention. No registrations, protocols, analysis plans, data sets, or preprints were found after 6 and 12 months, respectively. The participants’ perceptions of the current research evaluation system and on the OS practices and RRPs changed positively with the intervention. Also, the intention to adopt practices like registration, protocol and preprint publications has noticeably increased after the course. Conclusions The number of participants’ OSF outputs showed little or no improvement after the intervention. The most important impact difference could be identified in terms of the participants’ perceptions and intentions to adhere to such practices in the future.
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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 | MetaresearchOpen science Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | MetaresearchOpen science Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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, 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".