Bibliographic record
Abstract
Ethiopia was among the first countries that applied for external loan from the then newly created IMF in the early post WWII periods. Before 1945, the country sought defense-related external assistances. In the post war periods, however, the need for external borrowings arises due to saving-investment gaps, export-import gaps and financing fiscal budget deficits. Nonetheless, the problem of debt burden is a post 1973/74 periods phenomenon. During the imperial period (pre-1973/74), the rate of growth exceeded the cost of borrowing; thus debt service obligations were honored without any strain. But the story went different during Derg Regime; the growth to debt correlation turned negative and reached the stage where the country cannot survive without it. During the post Derge periods, especially in the early 1990s, quarter of the government’s total expenditure was financed from external grants and loans. In the years later, though the economy has performing vigorously but the burdens seem unrelenting. Hence, this study analyzed these facts by assessing the impacts of external debt on investment using time series macroeconomic data for the period 1974/75-2008/09.
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 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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".