The Helping Model of Interpersonal Communication: Viable Alternatives for Teacher Education Programs
Bibliographic record
Abstract
This article criticizes the extensive use of the helping model for interpersonal communication courses in teacher training programs. As one of several alternative models, the helping model is endorsed; as the sole model, it is criticized. While the humane goals of the helping model may be retained, it is argued that diverse means for attaining humane goals be utilized. The alternatives to the helping model discussed include the psychological perspectives of Maslow and Clarizio and Goldstein , the perspectives involving the management of human and public relations of Galleraman and Cutlip and Rapaport, and the rhetorical perspectives of Frye and Andersen and Freely. The article concludes with a reminder of the benefits associated with a limited use of the helping model for interpersonal courses in teaching programs and the burdens associated with the unlimited use of the helping model.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".