Welcome letter by the new editors
Bibliographic record
Abstract
Starting from 2022, we are taking over the role of Co-Editors-in-Chief of Social Psycho logical Bulletin.We are honored and delighted to serve the journal for the next five years, after the outstanding leadership of Michał Parzuchowski and Marcin Bukowski, outgoing Editors-in-Chief (2017-2021).Inspired by the vision of Maria Lewicka, who was the founding Editor-in-Chief (2006-2016), Michał and Marcin introduced far-reaching changes that have already produced visible results.In short, the previous team managed to successfully transform SPB from a solid but local Polish journal in social psychology to a truly international journal making it relevant to a global audience.As a direct result of Marcin and Michał's impressive efforts, fifteen issues that have been published since the transformation to an international journal included more than a hundred articles authored by 202 researchers from 24 countries.Thanks to the collab oration with Psychopen.euand the help of generous sponsors (above all, the Polish Social Psychological Society, the founder and owner of the title), the journal is now fully open access and without any costs for readers and authors.As such, it satisfies the highest -diamond gold -Open Access model.Importantly, that was not the only change initiated by the previous team toward more open and transparent journal practi ces.Social Psychological Bulletin has been strongly engaged in promoting open science practices (e.g., pre-registration, open data, open materials) with the aim of implementing the highest standards from the Transparency and Openness Promotion (TOP) guidelines (https://topfactor.org/).We would like to thank Michał and Marcin and all past Editors of SPB for all the work they put in to turning the journal into a significant international outlet for important
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
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 | 0.006 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.026 | 0.026 |
| Insufficient payload (model declined to judge) | 0.042 | 0.040 |
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".