Advancing Diversity, Equity, and Inclusion in School Psychology Science and Scholarship: Changing Training and Practice in the Field of School Psychology
Bibliographic record
Abstract
The intentional and sustained actions to advance diversity, equity, and inclusion (DEI) in school psychology science and scholarship, will have reciprocal and dynamic influences on graduate preparation and practice. Herein, the School Psychology Review leadership team provides reflections on several of our intentional efforts, to date, to advocate for and advance DEI in school psychology scholarship, and the associated implications for graduate preparation and practice. Contemporary actions of the School Psychology Review leadership team have included; (a) establishing commitments to advocating for and advancing DEI as the foundation of our scholarship; (b) diversifying journal leadership and editorial board members to reflect the diverse student body school psychologists serve; (c) preparing future diverse journal leadership through mentored editorial fellowship programs, and a student editorial board with members from diverse backgrounds; (d) featuring special topics relevant to further understanding and supporting diverse and minoritized children, youth, families, and school communities; (e) providing professional-development opportunities and resources; (f) implementation of Open Science opportunities in the journal, (g) implementing triple anonymous peer review to reduce bias, and (h) implementing a journal action plan focused on advancing DEI. Collectively these efforts are aimed to influence positive change in advancing and sustaining DEI efforts in school psychology science, scholarship, graduate preparation and practice.
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 | 0.187 | 0.290 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.018 | 0.023 |
| Scholarly communication | 0.029 | 0.016 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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, 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".