Bibliographic record
Abstract
Abstract Kenneth W. Spence was born in Chicago in 1907, but his family soon moved to Montreal where he spent most of his early years. He attended McGill University, graduated in 1929, and went on to earn a master's degree in 1930. He completed his graduate work at Yale, primarily under the direction of Robert Yerkes, and he was also influenced by Clark Hull. Hence his early research was with primates and was focused on learning and visual discrimination. Spence received his PhD from Yale in 1933 and then moved to the Yale (later Yerkes) Laboratory of Primate Biology in Orange Park, Florida. He worked there for four years, after which he accepted his first faculty position, a one‐year temporary appointment, in psychology at the University of Virginia, where he spent the 1937–1938 academic year. In 1938, he moved to the University of Iowa (then the State University of Iowa), where he remained until 1964. He moved to the University of Texas in 1964 and stayed there until his death in Austin in 1967. In 1959, he married Janet Taylor Spence, who has had a long and distinguished career of her own.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.575 | 0.313 |
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".