La mediazione della Santa Sede nel processo di normalizzazione delle relazioni bilaterali cubano-statunitensi
Bibliographic record
Abstract
The mediation of the Holy See in the process of normalization of Cuban-American bilateral relations ABSTRACT: This article aims to illustrate the fundamental stages and final moments of the singular and complex mediation conducted by the Holy See in the Cuban-American dispute, whose greatest success was the signing in the Vatican in 2014 of a protocol for the normalization of relations bilateral agreements interrupted in the aftermath of the Castro Revolution. In particular, the specificity, in terms of diplomatic dynamics, of this pontifical initiative is analysed, which inaugurated a new phase of negotiations in the stagnant talks that had already begun secretly in Canada between the two parties in 2011. Finally, the system of agreements of medium level concluded between the parties after the re-establishment of normal diplomatic channels, achieved thanks to the proactive role of the Pope and Vatican diplomacy. SOMMARIO: 1. L’attitudine della Santa Sede nell’affaire cubano. Prodromi e primi segnali di disgelo - 2. Lo stallo dei negoziati tra Washington e L’Avana e l’intervento vaticano. La proposta di facilitazione di Papa Francesco - 3. Portata e natura dell’iniziativa pontificia: ‘mediazione’ o ‘buoni uffici’? - 4. Conclusione dell’accordo e ripristino di rapporti diplomatici e bilaterali - 5. Notazioni finali.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".