How Recreation(al) Therapy/Therapeutic Recreation Academic Programs Structure the NCTRC-Eligible Internship into their Curricula
Bibliographic record
Abstract
Recreational Therapy/Therapeutic Recreation (RT) academic programs provide opportunities for students to further develop competencies through the NCTRC- eligible internship prior to graduation. The NCTRC- eligible internship experience is the third focus of the American Therapeutic Recreation Association’s Academic Action Task Force study to understand the landscape of RT academic program fieldwork experiences in the United States and Canada. Out of a total of 95 RT academic programs, 54 programs responded to an online questionnaire about the fieldwork opportunities provided to students. This brief report discusses the results of the NCTRC-eligible internship experiences in three areas: Pre-Internship Preparation, Program Eligibility Factors, and the NCTRC- eligible Internship Experience. Results indicated that most programs provide some level of support in finding, applying to, and securing internship sites; require students to have the majority of the coursework completed, a minimum program GPA of 2.0, completion of a 12-credit internship; and, evaluate learning outcomes through mid- and final evaluation reports. Areas of variability remain, such as site supervisor requirements and course requirements. Recommendations are made for further inquiry related to NCTRC-eligible internship fieldwork education.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".