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Record W4244113741 · doi:10.1037//0003-066x.55.10.1105

Hunger, eating, and ill health.

2000· article· en· W4244113741 on OpenAlex
John P. J. Pinel, Sunaina Assanand, Dan Lehman

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

VenueAmerican Psychologist · 2000
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOverconsumptionAnorexia nervosaScarcityPsychologyPerspective (graphical)Set (abstract data type)Variety (cybernetics)Economic shortageFood shortageEating disordersDevelopmental psychologySocial psychologyPsychiatryEconomicsBiologyEcologyProduction (economics)Computer scienceGovernment (linguistics)

Abstract

fetched live from OpenAlex

Humans and other warm-blooded animals living with continuous access to a variety of good-tasting foods tend to eat too much and suffer ill health as a result--a finding that is incompatible with the widely held view that hunger and eating are compensatory processes that function to maintain the body's energy resources at a set point. The authors argue that because of the scarcity and unpredictability of food in nature, humans and other animals have evolved to eat to their physiological limits when food is readily available, so that excess energy can be stored in the body as a buffer against future food shortages. The discrepancy between the environment in which the hunger and eating system evolved and the food-replete environments in which many people now live has led to the current problem of overconsumption existing in many countries. This evolutionary perspective has implications for understanding the etiology of anorexia nervosa.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.376
Teacher spread0.353 · 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