A Causal Model to Compare the Extent of Undergraduates’- Postgraduates’ Impact on Unemployment in Uganda
Bibliographic record
Abstract
The combination of technological unemployment and oversupply of graduates has increased competition in the labour markets. Postgraduates have been noted to hold more than one job and in some cases apply for jobs meant for undergraduates. Could this imply that post graduates have created more overall unemployment than undergraduates have, in the Ugandan labour market? This is the novel of this study. This was accomplished by a statistical model that comparatively analysed the bi-causal effect of postgraduates on unemployment; versus effect of undergraduates on unemployment. As such, the study utilised Uganda’s secondary data from 1991 to 2017, and employed the Vector Error Correction (VECM) model. The results of the study showed the existence of a long run impact of both the postgraduates and undergraduates on overall unemployment, but an insignificant impact in the short run. The postgraduates had a greater impact on unemployment in the long run, than the undergraduates. The study therefore reveals an affirmative answer to the aforementioned question.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".