Managing Conflict at Institution/s of Higher Learning: A Post-Positivist Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Institutions of Higher Learning in South Africa annually face challenges that often lead to student protests and demonstrations, mostly at the beginning of every academic year, which adversely impact the smooth running of academic programs. Stakeholders’ expectations were at the apex of causes that destabilise the academic environment, academic almanac and the overall academic professional reputation. The volatility of this kind retards productivity and negatively affects many tertiary institutions across the Country. This empirically grounded paper focuses on conflicting variables amongst universities, but with reference to an Eastern Cape University in South Africa spread across its Campuses. Adopting the post-positivist approach, this study obtained data from over 180 respondents and the data was analysed by using descriptive and inferential statistics, including analyses of variance and Pearson Product Moment correlations. In addition, content analysis techniques were used to analyse the data collected from the unstructured questionnaire. In this empirical study the findings highlighted two major variables that gave rise to conflicts, escalation of strikes and demonstrations at Higher Institutions of learning and recommend a conflict management style apposite for handling the conundrum. The factors dealt with in this study are not peculiar to the institution studied, but are analogous to other institutions. The findings also underscored Integrating conflict management as the most commendable style for managing conflicts at institutions of higher learning.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it