"Kidding Story Not a Kidding”: The Development of Process Framework for Enhancing Awareness of Creative Communication and Empathy in the Thai Social Context
Bibliographic record
Abstract
Kidding remarks in Thai social contexts are often perceived as trivial. However, frequent occurrences may lead to verbal bullying, particularly when the communicator does not consider the feelings of others. This study aims to develop a process framework to enhance awareness of creative communication and empathy in Thai social contexts. Additionally, it seeks to evaluate the experimental results and the disseminated application of the framework in promoting awareness of creative communication and empathy. The tools employed include: 1) a process framework for fostering awareness of creative communication and empathy in Thai social contexts, 2) a creative communication awareness scale, and 3) an empathy measurement scale. Statistical analyses consisted of mean, standard deviation, and repeated measures. The findings are as follows: 1) The process framework for promoting awareness of creative communication and empathy in Thai social contexts is titled “PUETSS.” 2) Experimental and extended applications of the framework revealed statistically significant improvements in students’ awareness of creative communication and empathy at the .05 level. These findings suggest that fostering awareness in communication encourages individuals to think before they speak and consider others’ feelings, ensuring that “kidding” does not harm others.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".