Governance of Somali Tertiary Education Systems: A Case Study in Complexity
Bibliographic record
Abstract
Governance of Tertiary Education Systems (TES) in Somalia and how the system of coordination described by Clark (1983) which tries to introduce order of the three dominating forces of educational system: “the state, the market and oligarchy”, is examined in this paper. How comparatively Higher Education Systems (HES) is structured, or inadvertently coordinated, arranged and rearranged since the formal Higher Education (HE) has been introduced into Somali nation state will also be examined from a vantage point of whether this trend is in line with other nations’ conventional TES. In the first twenty years, the dynamic system of coordination, which according to Clark introduces order into the three dominating forces of the Somali educational system, could not have been possible, as only the state owned and bank-rolled all Higher Education Institutions (HEI) that existed at the time. Thus the “academic oligarchy and the market” took a secondary role. The incentive of job guarantees for the new graduates by the authority made difficult to estimate the ‘quality of the education’, which in turn, could have compromised their ability and efficiency in their professional contexts. In post-conflict Somalia, the higher education system has dramatically increased with over one hundred universities now open throughout the country with no or little regulations. This time round though, the other two educational forces, the market and oligarchy are playing pivotal roles while that of the government has disappeared. Over the years since the collapse of the state in 1991, the national government’s influence decreased ceding so much higher education space, to the five Federal Member States (FMSs). Thus, the situation fits with Clark’s dynamic model showing that it is a system capable of reflecting upon ongoing change within the overall socio-political situation. What seems to be developing in the Somali higher education context therefore, is a system in which each force is autonomous with no clear goals shared within the larger structure. As for tertiary education in general, complemented by the rapidly changing world of work, the consensus is 'Having the right qualifications, in the right subjects, from the right institutions' that will benefit all sectors of the economy. It is with that in mind that the disparity between the way in which HE is delivered and the world of work is also examined in this paper. If this important complementarity is not analyzed in the current situation of Somalia, it could pose huge problematic consequences for tertiary education in the country. It is the case that HEIs did not give deserved attention to job market demands as they hardly study that to better serve the needs of employers. collaborative initiatives between the Ministry of Education and Higher Education (MoEHE) and the private sector to support HE is being examined in the final part of this 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".