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Record W4410002731 · doi:10.1037/amp0001526

Publication trends for qualitative inquiry in American Psychological Association and Association for Psychological Science journals.

2025· article· en· W4410002731 on OpenAlexaff
Tamara Stecyk, Dennis C. Wendt, Sophie Blackmore

Bibliographic record

VenueAmerican Psychologist · 2025
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsMcGill University
Fundersnot available
KeywordsAssociation (psychology)Psychological sciencePsychologyProfessional associationScientific communicationPsychological researchClinical psychologySocial psychologyLibrary sciencePolitical sciencePsychotherapistPublic relations

Abstract

fetched live from OpenAlex

Framed against the long-standing dominance of quantitative methods in psychological science, this study examined contemporary publishing patterns for qualitative inquiry in American Psychological Association (APA) and Association for Psychological Science (APS) journals. We examined 19,012 publications across 95 APA and APS journals across four time points (2005, 2012, 2019, and 2022). The percentage of qualitative articles was determined using the methodology field value within APA PsycInfo, a process that we validated through a batch test. We also conducted a content analysis of journal mission statements and submission guidelines, and we made comparisons in light of journal impact factors. Our findings show a nearly threefold increase in qualitative publications accelerating over time from 2005 to 2022, albeit with wide variations depending on the type of journal. Qualitative-friendly journals were more likely to be published by APA, be specialty journals, be dedicated to diverse populations, and have lower impact factors. Conversely, qualitative research was less likely to be published in APS journals, core psychology journals, journals focused on general populations, and journals with higher impact factors (with some notable exceptions). We discuss these findings in terms of implications for the advancement of psychological science, including the discipline's need for development in qualitative training and expertise, its commitments to antiracism and anticolonialism, its fragmentation, and its equity in publishing. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

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 imitation

Not 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.

metaresearch head score (Codex)0.105
metaresearch head score (Gemma)0.345
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.555

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1050.345
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0290.057
Science and technology studies0.0020.003
Scholarly communication0.0090.007
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.002

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.

Opus teacher head0.387
GPT teacher head0.705
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainReporting
GenreEmpirical

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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