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Record W2114116188 · doi:10.1177/1745691610369469

Renovating the Pyramid of Needs

2010· review· en· W2114116188 on OpenAlexaff
Douglas T. Kenrick, Vladas Griskevicius, Steven L. Neuberg, Mark Schaller

Bibliographic record

VenuePerspectives on Psychological Science · 2010
Typereview
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental Health
KeywordsPyramid (geometry)PsychologyCognitive psychologyPhysics

Abstract

fetched live from OpenAlex

Maslow's pyramid of human needs, proposed in 1943, has been one of the most cognitively contagious ideas in the behavioral sciences. Anticipating later evolutionary views of human motivation and cognition, Maslow viewed human motives as based in innate and universal predispositions. We revisit the idea of a motivational hierarchy in light of theoretical developments at the interface of evolutionary biology, anthropology, and psychology. After considering motives at three different levels of analysis, we argue that the basic foundational structure of the pyramid is worth preserving, but that it should be buttressed with a few architectural extensions. By adding a contemporary design feature, connections between fundamental motives and immediate situational threats and opportunities should be highlighted. By incorporating a classical element, these connections can be strengthened by anchoring the hierarchy of human motives more firmly in the bedrock of modern evolutionary theory. We propose a renovated hierarchy of fundamental motives that serves as both an integrative framework and a generative foundation for future empirical research.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0010.005
Scholarly communication0.0020.006
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.141
GPT teacher head0.527
Teacher spread0.386 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations1,109
Published2010
Admission routes1
Has abstractyes

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