Sense of Community: Perceptions of “Inter-Intra” Collaborations in an Academic Environment through the Lenses of Botho Principles and the Field of industrial Psychology
Bibliographic record
Abstract
In the current study, I explored the concept of collaboration from Botho principles and the industrial psychology perspective in specific higher learning institutions. Using a qualitative approach, 13 participants performing academic and nonacademic roles formed part of the study. Overall, the participants experiences regarding collaboration in an academic environment are reported to be in the form of hared goals, sense of unity, diversity, and solution-driven teams. Further participants experiences in relation to collaboration is African cultureBotho principles. The latter were perceived contributors to collaboration within departments (intra); and few barriers to collaboration were discovered, such as criteria, lack of shared leadership, lack of collaboration champions or ambassadors. The concept of Botho is defined as a social contract of mutual respect, humanity, and responsibility that members have with one another often referred to as bringing in humanity onto processes or a set environment. Although there are commonalities between Botho and Ubuntu, they however have dissimilarities and are underpinned by different cultures and traditions. Ubuntu is seen often used by a slogan, “I am because you are”. Botho is Setswana or Sesotho concept while Ubuntu forms part of Nguni languages. The I then further conceptualize collaboration through the lens of industrial psychology from the results and offer future research recommendations in the current paper.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".