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Record W7119899368 · doi:10.1515/9783839472378-003

From One to(o) Many

2025· book-chapter· W7119899368 on OpenAlex
Filipa Queirós, Rafaela Granja

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuetranscript Verlag eBooks · 2025
Typebook-chapter
Language
FieldSocial Sciences
TopicDecolonial Thought and Epistemologies
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsSuspectContext (archaeology)Set (abstract data type)Criminal investigationIdentification (biology)NarrativePopulation

Abstract

fetched live from OpenAlex

Forensic DNA phenotyping (FDP) refers to a set of techniques that aim to derive probabilistic information about certain externally visible characteristics of suspects, such as eye, skin, and hair color, from biological samples.In forensic science, this technology is most commonly used to predict the appearance of an unknown suspect in criminal investigations.In this chapter, we examine the artistic exhibition Probably Chelsea and a real criminal case in Canada as platforms for discussing how, despite narratives claiming that FDP enables a fine-grained approach that might lead to the identification of a suspect, in practice this technology creates a coarse-grained context that casts suspicion on an entire population group.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.855
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.055
GPT teacher head0.293
Teacher spread0.238 · 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