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On Becoming a Qualitative Researcher: The Value of Reflexivity

2015· article· en· W27308458 on OpenAlexaff
Diane Watt

Bibliographic record

VenueThe Qualitative Report · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsReflexivityQualitative researchValue (mathematics)PhenomenonEpistemologyNarrativeProcess (computing)Field (mathematics)Task (project management)SociologyEngineering ethicsPsychologyComputer scienceSocial scienceManagement

Abstract

fetched live from OpenAlex

Learning how to conduct qualitative research may seem daunting for those new to the task, especially given the paradigm ’s emphasis on complexity and emergent design. Although there are guidelines in the literature, each project is unique and ultimately the individual researcher must determine how best to proceed . Reflexivity is thus considered essential, potentially facilitating understanding of both the phenomenon under study and the research process itself . Drawing upon the contents of a reflective journal, the author provides an inside view of a first project, making connections between theory and practice. This personal narrative highlights the value of reflexivity both during and after a study, and may help to demystify the research process for those new to the field.

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)0.468
metaresearch head score (Gemma)0.539
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.532
Threshold uncertainty score0.655

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4680.539
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.004
Science and technology studies0.0200.141
Scholarly communication0.0390.038
Open science0.0070.029
Research integrity0.0110.027
Insufficient payload (model declined to judge)0.0050.002

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 head0.858
GPT teacher head0.753
Teacher spread0.104 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations600
Published2015
Admission routes1
Has abstractyes

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