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Time Budgets, Diaries, and Analyses of Concurrent Practice Activities

2006· book-chapter· en· W60852115 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

VenueCambridge University Press eBooks · 2006
Typebook-chapter
Languageen
FieldPsychology
TopicFlow Experience in Various Fields
Canadian institutionsQueen's University
Fundersnot available
KeywordsRelevance (law)Perspective (graphical)Dimension (graph theory)Time perspectivePsychologyComputer scienceSocial psychologyArtificial intelligencePolitical scienceMathematics

Abstract

fetched live from OpenAlex

Time is an inescapable dimension of all human activity. What time of day, month, and year, for how long, before or after what other activity, how long before or after another given activity and how often, are questions answerable for all activities. The relevance of each question varies with one's perspective on the activity. Time-use methodology can provide rich, objective, and replicable temporal information to answer the questions posed, hence providing a basis for forming and/or collaborating empirical judgments. Coupled with other objective and subjective contextual information on each incident of an activity, time-use methodologies can generate invaluable information for understanding activities and human behavior. Time-use studies show how people use their time. Minimally, they show what activities people do, while maximally, they can show what people are doing, where they are, who they are with, and how they feel.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.035
GPT teacher head0.287
Teacher spread0.252 · 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