Temperamental workers: Psychology, business, and the Humm-Wadsworth Temperament Scale in interwar America.
Bibliographic record
Abstract
This article traces the history of a popular interwar psychological test, the Humm-Wadsworth Temperament Scale (HWTS), from its development in the early 1930s to its adoption by corporate personnel departments. In popular articles, trade magazines, and academic journals, industrial psychologist Doncaster Humm and personnel manager Guy Wadsworth trumpeted their scale as a scientific measure of temperament that could ensure efficient hiring practices and harmonious labor relations by screening out "problem employees" and screening for temperamentally "normal" workers. This article demonstrates how concerns about the epistemological and scientific credibility of the HWTS were intimately entangled with concerns about its value to business at every step in the test's development. The HWTS sought to measure the emotional and social dimensions of an individual's personality so as to assess their suitability for work. The practice of temperament testing conjured a vision of the subject whose emotional and social disposition was foundational to their own capacity to find employment, and whose capacity to appropriately express, but regulate, their emotions was foundational to corporate order. The history of the HWTS offers an instructive case of how psychological tests embed social hierarchies, political claims, and economic ideals within their very theoretical and methodological foundations. Although the HWTS itself may have faded from use, the test directly inspired creators of subsequent popular personality tests, such as the Minnesota Multiphasic Personality Inventory and the Myers-Briggs Type Indicator. (PsycINFO Database Record
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".