MétaCan
Menu
Back to cohort
Record W3206493376 · doi:10.1177/10323732211040272

The centrality of ethical utterances within professional narratives

2021· article· en· W3206493376 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

VenueAccounting History · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicComputational and Text Analysis Methods
Canadian institutionsUniversity of CalgaryYork University
Fundersnot available
KeywordsCentralitySituational ethicsVariety (cybernetics)Professional ethicsNarrativeEthical codeSociologyMeta-ethicsProfessional conductEngineering ethicsPublic relationsInformation ethicsPsychologyPolitical scienceSocial psychologyLinguisticsLawComputer science

Abstract

fetched live from OpenAlex

This study examines the centrality of ethics within editorials published in the Canadian Institute of Chartered Accountants’ professional journal, CA Magazine, over the 1912 to 2010 period. Starting from the twin assumptions that editorials speak about appropriate professional behavior using a variety of words such as ‘ethics,’ ‘conduct,’ and ‘codes,’ and that appropriate professional behavior is situational, we use topic modeling techniques to identify these dimensions of ethical discourse. We then use social network analysis methods to map the position and centrality of ethics within the editorials across time. The results show that enunciations about appropriate professional conduct are broader than simply enunciations using the word ‘ethics’. The results also highlight that ethical utterances become more central, not less central, over time.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.042
GPT teacher head0.374
Teacher spread0.331 · 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