Society for the Improvement of Psychological Science Global Engagement Task Force Report
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Society for the Improvement of Psychological Science (SIPS) is an organization whose mission focuses on bringing together scholars who want to improve methods and practices in psychological science. The organization reaffirmed in June 2020 that “[we] cannot do good science without diverse voices,” and acknowledged that “right now the demographics of SIPS are unrepresentative of the field of psychology, which is in turn unrepresentative of the global population. We have work to do when it comes to better supporting Black scholars and other underrepresented minorities.”The purpose of the Global Engagement Task Force, started in January 2020, was to explore suggestions made after the 2019 Annual Conference, held in Rotterdam, the Netherlands, around inclusion and access for scholars from regions outside of the United States, Canada, and Western Europe (described in the report as “geographically diverse” regions), a task complicated by the COVID-19 pandemic and civil unrest in several task force members’ countries of residence. This report outlines several suggestions, specifically around building partnerships with geographically diverse open science organizations; increasing SIPS presence at other, more local events; diversifying remote events; considering geographically diverse annual conference locations; improving membership and financial resources; and surveying open science practitioners from geographically diverse regions.
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.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it