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Record W4379161567 · doi:10.1177/10778004231176282

The Art of Data Analysis: Disturbing Knowledge and Performing Critical Inquiry

2023· article· en· W4379161567 on OpenAlexafffund
Mirna E. Carranza

Bibliographic record

VenueQualitative Inquiry · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsMcMaster University
FundersArts Research Board, McMaster University
KeywordsEmbodied cognitionSociologyPoliticsSocial justiceWhite (mutation)ImmigrationEpistemologyAestheticsSocial sciencePolitical scienceArtLaw

Abstract

fetched live from OpenAlex

Using theater and performance, the building of “We are not the Others” brought into discussion—How does the researcher ethically “code” data to re-present the stories of Women Immigrants who are understood as the Other to achieve the social justice goals? This article explores these questions and asks, “What is the purpose and politics of an embodied performance of/by the Other for White audiences?” These questions framed the processes of creating the re-telling of stories and were integral to the ethical engagement of audiences in a way that drew them in, to understand their own implications.

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 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)0.053
metaresearch head score (Gemma)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0530.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.009
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.659
GPT teacher head0.677
Teacher spread0.017 · 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; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
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

Citations2
Published2023
Admission routes2
Has abstractyes

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