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Record W3161169094 · doi:10.5296/jse.v11i2.18496

Rigorous Phenomenography: A Conceptual Model

2021· article· en· W3161169094 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 Studies in Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsNipissing UniversityLaurentian University
Fundersnot available
KeywordsPhenomenographyGeneralizability theorySituatedReliability (semiconductor)Qualitative researchProcess (computing)Conceptual modelPsychologyValidityManagement scienceEpistemologyComputer sciencePedagogySociologyEngineeringSocial sciencePsychometricsDevelopmental psychologyArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

This paper presents a visual conceptual model for the qualitative research approach referred to as phenomenography. The static and recursive stages of a rigorous phenonemographical approach to research are outlined in detail. Using the example of a research study situated in pre-service teacher education, the authors explain how the fifteen distinct steps of phenomenographic research should be addressed with attention to the sequencing of these steps to support reliability and rigor of the research process and validity and generalizability of the outcome spaces that may result from the use of phenomenography.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.126
GPT teacher head0.495
Teacher spread0.370 · 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