Editorial: Recommendations on inclusive language and transparent reporting relating to diversity dimensions for the <i>Journal of Pediatric Psychology</i> and <i>Clinical Practice in Pediatric Psychology</i>
Bibliographic record
Abstract
In 2023, the incoming Editors of the Journal of Pediatric Psychology (JPP) and Clinical Practice in Pediatric Psychology (CPPP), Drs. Avani Modi and Christina Duncan, respectively, both identified enhancing reporting practices for diversity, equity, and inclusion (DEI) in pediatric psychology as a top priority (Duncan, 2023; Modi, 2023). These efforts build upon a 2021 JPP editorial led by Dr Tonya Palermo and a team of Associate/Assistant Editors declaring a public commitment to being an anti-racist journal and providing guidance for reporting on race and ethnicity in JPP articles (Palermo et al., 2021). The rationale for these efforts stems from the likelihood that (a) terminology used in previous articles published in our journals resulted in harm to people with marginalized identities, (b) past research lacks generalizability of results because study samples lacked representativeness, and (c) past articles published in our journals likely perpetuated white supremacy culture by using white culture as the norm and comparing other cultures/identities to the white norm. Moreover, our current efforts strive to address a broader set of diversity dimensions, using the ADDRESSING Framework (Hays, 2016) as guidance, with the goal of enhancing the rigor and inclusiveness of pediatric psychology science. Thus, the Editors convened a working group of current and past JPP and CPPP Associate Editors and Editorial Board members, as well as DEI content experts. The aims were to generate consistent reporting guidelines for diversity dimensions across the journals and to inform best practices for future research in pediatric psychology. The working group found many detailed, existing checklists and guidelines on inclusive language and transparent reporting relating to DEI (American Psychological Association, 2023b; Buchanan et al., 2021; Letzen et al., 2022; Matsui et al., 2020; Miller et al., 2019; Williford et al., 2023b). However, no comprehensive guidelines were available that captured the specific context of pediatric psychology (e.g., developmental/family considerations), while also being broadly applicable across the field (e.g., not focused on a specific condition or symptom).
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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 | 0.120 | 0.511 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.027 | 0.018 |
| Open science | 0.012 | 0.007 |
| Research integrity | 0.045 | 0.032 |
| Insufficient payload (model declined to judge) | 0.043 | 0.065 |
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".