General Aptitude Test Battery (GATB): Use of Obsolete Tests, Data, and Beliefs Causes Harm
Bibliographic record
Abstract
Abstract Psychologists use obsolete intelligence tests and data to make false research and clinical claims such as (a) undergraduate students’ IQ is between 115 and 130 points, (b) correlations between IQ and years of education are well above 0.50, and (c) 16% of workers in any occupation are prevented from performing their job due to their low IQ. In this study, we examine one of the obsolete tests, General Aptitude Test Battery Canadian Edition (GATB CDN), derived from the United States Employment Service GATB but normed on the Canadian General Working Population (GWP) sample. We briefly review the history of the GATB and report on a new study in which we examined how university students today perform on the GATB CDN, some 40 years after it was normed. Our results show that undergraduate university students today scored on average about 1 SD (15 IQ points equivalent) below the 1985 GATB CDN GWP norms. In contrast, these same students scored on average 103 IQ points on Shipley-2, which was normed in 2008 on a US population sample. Our results demonstrate that the GATB CDN norms have become outdated and obsolete. In turn, opinions issued by vocational counselors, vocational psychologists, neuropsychologists, and forensic psychologists based on the GATB CDN obsolete norms are invalid, misinformation, unscientific, and pseudoscience. We conclude that using outdated and obsolete IQ data to make disparaging statements about examinees’ IQ and ability to do specific jobs is harmful, incompetent conduct, and malpractice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".