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Record W2782102453 · doi:10.1177/1747016117750208

Ethics review and freedom of information requests in qualitative research

2018· article· en· W2782102453 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueResearch Ethics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsUniversity of TorontoUniversity of Winnipeg
Fundersnot available
KeywordsFreedom of informationVettingTransparency (behavior)Government (linguistics)BureaucracyPolitical scienceEngineering ethicsInformation ethicsPublic relationsQualitative researchCitizenshipSociologyResearch ethicsLawSocial sciencePoliticsEngineering

Abstract

fetched live from OpenAlex

Freedom of information (FOI) requests are increasingly used in sociology, criminology and other social science disciplines to examine government practices and processes. University ethical review boards (ERBs) in Canada have not typically subjected researchers’ FOI requests to independent review, although this may be changing in the United Kingdom and Australia, reflective of what Haggerty calls ‘ethics creep’. Here we present four arguments for why FOI requests in the social sciences should not be subject to formal ethical review by ERBs. These four arguments are: existing, rigorous bureaucratic vetting; double jeopardy; infringement of citizenship rights; and unsuitable ethics paradigm. In the discussion, we reflect on the implications of our analysis for literature on ethical review and qualitative research, and for literature on FOI and government transparency.

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)0.545
metaresearch head score (Gemma)0.445
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.5450.445
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.022
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.013
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 head0.823
GPT teacher head0.770
Teacher spread0.053 · 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