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
Abstract The relationship between foreign direct investment (FDI) and military spending in the Middle East and North Africa (MENA) region is complex and multifaceted. High levels of military spending can deter foreign investors, as it creates an uncertain and potentially volatile investment climate. However, countries that invest in their military infrastructure and capabilities may be seen as more stable and secure, which can attract foreign investors. Taking into account several factors that can influence this relationship, including political stability, security concerns, and economic factors, this work analyzes whether military spending attracts foreign capital into the region. Using a dynamic panel data methodology along with other relevant macroeconomic variables, results show that the military expenditure has a positive and significant impact on FDI inflows into the MENA region. The paper highlights the fact that policymakers in the region must carefully balance military spending with investments in other areas of the economy in order to create a stable and favorable investment climate that attracts foreign investors and contributes to long‐term economic growth and development achieving both security and welfare.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.010 |
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