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Record W2023776254 · doi:10.1080/09084280701719211

The Flynn Effect Revisited

2007· review· en· W2023776254 on OpenAlexaff
Elbert W. Russell

Bibliographic record

VenueApplied Neuropsychology · 2007
Typereview
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsPsychologyWechsler Adult Intelligence ScalePlateau (mathematics)Intelligence quotientBorderline intellectual functioningDevelopmental psychologyCognitionPsychiatryMathematics

Abstract

fetched live from OpenAlex

The Flynn Effect postulates that intelligence is increasing over time. However, as an environment becomes optimal, a plateau occurs when general growth becomes largely determined by genetics. There is evidence that such a plateau is occurring for intelligence in countries with optimal social environments. In the United States, examination of adult Wechsler test scores between normings indicates a reduction of the FSIQ increase such that average FSIQ would plateau about 2024. However, the WAIS-III norming process eliminates many types of subjects with possible brain impairment. This probably raises the average FSIQ level. With an increase of only 1 FSIQ point in 16 years, a plateau in the Flynn Effect would have been reached in 2004.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0110.002

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 head0.083
GPT teacher head0.418
Teacher spread0.335 · 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 designNot applicable
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

Citations12
Published2007
Admission routes1
Has abstractyes

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