The Theory of Planned Behavior: Predicting Teachers’ Intentions and Behavior during Fitness Testing
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
The twofold purpose of this study was to develop and validate an instrument that assessed teachers’ intentions, attitudes, subjective norm, and perceived behavior control to administer fitness tests effectively, and to determine how well the instrument could predict teachers’ intentions and actual behavior based on Ajzen’s (1985, 1991) theory of planned behavior. In the development phase of the study, 104 physical educators completed the pilot version of the survey to refine the instrument. In the prediction of behavior phase of the study, a convenience sample of 195 physical educators completed (a) the Teachers’ Intentions to Administer Physical Fitness Tests Effectively (TIAPFTE) before fitness testing and (b) a behavior self-report after they administered fitness testing. Standard multiple regression analyses showed perceived behavioral control and attitude significantly predicted intention. Furthermore, results showed that attitude significantly predicted teachers’ behavior directly.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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