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Record W3099638507 · doi:10.1177/1558689820970692

Strange Bedfellows: Exploring Methodological Intersections Between Realist Inquiry and Structural Equation Modeling

2020· article· en· W3099638507 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

VenueJournal of Mixed Methods Research · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsStructural equation modelingEpistemologyField (mathematics)Critical realism (philosophy of perception)SociologyMultimethodologyLatent variableRealismManagement scienceComputer scienceSocial scienceMathematicsPhilosophyArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Realist inquiry, based on the philosophy of critical realism, focuses on exploring the underlying mechanisms that drive social phenomena. Structural equation modeling is a collection of quantitative analytical methods that take a theory-based, confirmatory approach to examining statistical relationships between measured (observable) and underlying (latent) variables. Despite originating from different scientific traditions, the apparent similarities between these two approaches hold promise for their combination in mixed methods research. This article contributes to the field of mixed methods research by exploring their potential synergies, how each approach could contribute to the other, and proposing a framework for their combinations in mixed methods research, which has implications in terms of the implied and explicit ontological and epistemological positionings of these two approaches.

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.

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)0.073
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0730.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.974
GPT teacher head0.734
Teacher spread0.240 · 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