The Rise Of Null Hypothesis Significance Testing As The Gold Standard In Psychology, 1940-55
Bibliographic record
Abstract
In the midst of the ongoing replication crisis, it is more important than ever for psychologists to look critically at methodology. Nearly every psychologist uses null hypothesis significance testing (NHST) to analyze and draw conclusions from quantitative data, despite its imperfections and the heavy criticisms it has received, particularly in recent years. Though NHST is usually taught as a strictly formalized, “objective” procedure inherent to the field, it was only introduced to psychology in the 1930s. The method reached its current status of ubiquity during the so-called “inference revolution” of 1940-55 (Gigerenzer & Murray, 1987). However, the means through which this revolution occurred remain unclear. By reviewing course catalogues from six major Canadian universities from 1940-55 and situating my findings in the broader historical context, I aim to disentangle how, and why, NHST became the gold standard of psychological statistics during this time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".