Enhancing team building in project-oriented organizations: An arts-based approach
Bibliographic record
Abstract
Background: This study investigates the impact of an arts-based approach on team building within project-oriented organizations, focusing on Solico Kalleh Food Industry Group. Objective: The research aims to evaluate how artistic interventions affect team dynamics, including formation, conflict resolution, and overall performance. Methods: An arts-based research methodology was employed, assessing variables such as forming, storming, norming, performing, internal factors, and external factors. A paired t -test analysis was conducted to evaluate the impact of these interventions. Results: The results indicated a statistically significant positive effect on the storming variable, suggesting improved team dynamics and conflict resolution. However, decreases were observed in norming, performing, internal factors, and external factors, indicating the need for careful application of artistic methods. The forming variable showed a slight non-significant increase. Conclusions: The study highlights the potential of arts-based approaches to enhance creativity, cohesion, and conflict resolution in team building. However, strategic and nuanced implementation is necessary to balance the impact on team dynamics throughout the project lifecycle. Future research should refine these strategies for optimized integration, ultimately enriching organizational dynamics and fostering successful project outcomes.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".