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Record W4416203009 · doi:10.1080/23299460.2025.2582306

Frankenwords or, responsible innovation for the humanities

2025· article· en· W4416203009 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 Responsible Innovation · 2025
Typearticle
Languageen
FieldPsychology
TopicScience Education and Perceptions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsResponsible Research and InnovationNeologismNormativeArgument (complex analysis)Perspective (graphical)DutyMythologyHarm

Abstract

fetched live from OpenAlex

This perspective is an exercise in reflexivity. The field of Responsible Research and Innovation commonly provides normative analyses of the STEM disciplines. I am asking here: can an argument be made to pay more attention to innovation in the humanities, for example neologisms, metaphors and slogans? I use the history of the neologism Frankenfood to link the responsibilities of STEM and non-STEM disciplines. The history of this word in combination with the history of its inspiration, Mary Shelley’s novel (Frankenstein; Or, the Modern Prometheus), provides a rich tapestry linking the verbal with the physical. Two ethical themes already seem present in the original Promethean myths (Prometheus plasticator and Prometheus pyrphoros), the responsibility of designing creations well, and the follow-up duty of care for the creations. I hope the focus on the persistence and potential harm of memes will promote a discussion of responsible innovation in the humanities.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.157
GPT teacher head0.462
Teacher spread0.305 · 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