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Record W4395954995 · doi:10.1080/14780887.2024.2347581

Zooming into qualitative research: online adaptation of the action-project method research design

2024· article· en· W4395954995 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQualitative Research in Psychology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAction researchQualitative researchAdaptation (eye)PsychologyAction (physics)Research designZoomSociologyPedagogyEngineeringSocial science

Abstract

fetched live from OpenAlex

The Action-Project Method (A-PM) is a comprehensive qualitative research method guided by Contextual Action Theory, which has been successfully employed to study the goal-directed actions of dyads (e.g. parent-child pairs; couples). In this article, we discuss how we adapted the A-PM to successfully collect rich longitudinal qualitative data using remote video-based data collection procedures. After describing the A-PM in detail, we draw upon an example from a recent study which successfully implemented this methodology over a video-conference platform. Data collection and analysis procedures are described, as well as the methodological integrity of the A-PM. To facilitate consideration of the appropriateness of the remote methodological adaption to the A-PM, we discuss several practical strengths and limitations. Ultimately, we maintain that it is possible and viable to complete this method online. We hope to inform a new generation of researchers about the adaptability of the A-PM research design to remote data collection procedures.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.412
metaresearch head score (Gemma)0.048
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.382
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4120.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.016
Science and technology studies0.0020.009
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.929
GPT teacher head0.814
Teacher spread0.115 · 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