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Record W3101236358 · doi:10.29173/cais1116

Forked Times: Documenting “Ordinary Time” in Everyday Life

2020· article· fr· W3101236358 on OpenAlexafffundvenue
Pamela J. McKenzie

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicDiverse Cultural and Historical Studies
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsHumanitiesHistoryPhilosophy

Abstract

fetched live from OpenAlex

“Ordinary” time is commonly defined as time that is neither holidays nor emergencies, which suggests that “ordinary time” events are routine rather than singular. An analysis of how people document events in “ordinary” time, however, shows that the stream of “ordinary” time has multiple forks; that ordinary does not necessarily mean predictable, and that both vacations and emergencies could, in certain circumstances, take on the character of routine rather than singular events. Le temps «ordinaire» est généralement défini comme un temps qui n'est ni des vacances ni des urgences, ce qui suggère que les événements «ordinaires» sont routiniers plutôt que singuliers. Une analyse de la manière dont les gens documentent les événements en temps «ordinaire» montre cependant que le flux du temps «ordinaire» a plusieurs fourchettes; cet ordinaire ne signifie pas nécessairement prévisible et que les vacances et les urgences pourraient, dans certaines circonstances, prendre le caractère d'événements routiniers plutôt que singuliers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0020.009
Scholarly communication0.0060.013
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.255
Teacher spread0.216 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI→Same topicDiverse Cultural and Historical Studies→French-language works237,207→