A statistical analysis of the use of a business game
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fred NoNurray of Rumble Oil and Refining Co. of Houaton, Taxaa, haa dona aoma raaaarch into the effectiveness of their business game.Hie was a paychologlcal reaaaroh project dealing with personal reaponses of partlclpanta to questions suoh asi "Are you satiafled with tha reaulta of thla quarter for your company?" or "Did you feel you were the only one of your team who knew what the right .1 decision waa on the declalon?"No publiahed data was ever found oonoeming this project.Some colleges such as Tulane Uhlveraity and Cornell Uhiveralty are conducting some research into the area of business gamea at the preaent.Also at Clarkson College under the leadership of Dr. L* W. Iferron reaaarchera are trying to validate the 2 results of their gaming experience.At Carnegie Tech under the leadership of Dr. Kal Cohen researchers are trying to determine how objective gaming ahould be used and where it fits into the larger con< text of their over-all training and educational activities.Thay are planning to ccxnpare effects of a very complex business game with the effects of simpler games.
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.
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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it