Vzpon in padec Alberta Fujimorija: avtoritarizem in protiteroristični ukrepi v Peruju
Bibliographic record
Abstract
Diplomska naloga obravnava vladavino Alberta Fujimorija v Peruju med letoma 1990 in 2000, s poudarkom na njegovih protiterorističnih ukrepih. V uvodnem delu je predstavljeno politično in ekonomsko stanje Peruja pred njegovim prihodom na oblast ter vzpon teroristične organizacije Sijoča pot. Sledi analiza Fujimorijevih ukrepov na pravnem, političnem, vojaškem, gospodarskem in medijskem področju, zlasti v kontekstu boja proti terorizmu. Naloga podrobneje preučuje njegove metode vladanja, kot so državni udar leta 1992, sprememba ustave in centralizacija oblasti. Posebno pozornost namenja njegovim ekonomskim ukrepom, znanim kot fujishock, ki so vključevali stabilizacijo gospodarstva in boj proti inflaciji. Opisane so tudi Fujimorijeve medijske strategije ter oblikovanje kulta osebnosti. V nalogi so obravnavani dolgoročni učinki njegove vladavine na perujsko politiko, gospodarstvo in družbo, s poudarkom na vprašanjih korupcije in neoliberalnih reform. Posebna osredotočenost je namenjena Fujimorijevim strategijam boja proti terorizmu, kot so ustanovitev posebnih vojaških enot in podpora lokalnim vaškim stražam. Diplomsko delo se dotakne tudi njegovega padca leta 2000 ter kasnejših sodnih postopkov proti njemu. Zaključek ponuja pregled Fujimorijeve politične zapuščine in njenega vpliva na sodobni Peru.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".