A formação conjunta no âmbito das informações militares
Bibliographic record
Abstract
Decorrente do atual contexto internacional, as informações militares enfrentam um grande desafio, que se traduz na habilitação dos seus recursos humanos, carentes de especialização nesta vertente. Com o presente trabalho pretende-se analisar o modelo formativo de informações militares, em uso nas Forças Armadas Portuguesas e verificar de que forma poderá ser otimizado. A metodologia de investigação seguiu a lógica de um raciocínio indutivo, assente numa estratégia qualitativa, baseando-se num desenho de pesquisa de estudo de caso, através de uma análise documental e de conteúdo, com recurso a entrevistas semiestruturadas efetuadas a especialistas em informações militares. Identificaram-se as lacunas patentes no presente modelo formativo, tendo por base as competências inerentes ao desempenho de funções de informações militares, bem como os exemplos de outros modelos formativos praticados por países amigos, são apresentadas propostas para a edificação de um modelo formativo de cariz conjunto, no seio das Forças Armadas Portuguesas. Concluiu-se que o modelo formativo atual se encontra descentralizado, sofrível de coordenação e complementaridade, sendo possível otimizá-lo através de uma reformulação assente em recursos e mecanismos já existentes, incrementando novos. Contribuindo assim, para um salto qualitativo, no sentido de garantir a harmonização do conhecimento e permitir o reconhecimento geral de uma competência específica. Abstract: Due to the current international context, Intelligence faces a great challenge, which translates into the qualification of its human resources, lacking in specialization. The intend of this work, is to analyze the Intelligence education model, in use in the Portuguese Armed Forces and to verify how it can be optimized. The research methodology followed the logic of an inductive reasoning, based on a qualitative strategy and a case study research design, through a documentary and content analysis, using semi-structured interviews with Intelligence specialists. The gaps in the national education model were identified, and based on the competencies inherent to the performance of Intelligence job descriptions, as well as examples of other friend countries education models, proposals are presented for the building of a joint education model within the Portuguese Armed Forces. It was concluded that the current education model is decentralized, suffering from coordination and complementarity, being possible to optimize it through a reformulation based on existing resources and mechanisms, increasing others, thus contributing to a qualitative leap, in order to ensure the harmonization of knowledge and allow the general recognition of a specific competence.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".