Securitatea și guvernanța spațiului cibernetic în Romania. Evaluare retrospectiva 2016-T1/2017-T1. (The Security and Governance of the Romanian Cyberspace. Retrospective Assessment 2016-Q1/2017-Q1)
Bibliographic record
Abstract
Romanian Abstract: Având la baza metodologia și grila de analiza cu indicatorii propuși in studiile anterioare, in cele ce urmeaza se analizeaza retrospectiv securitatea și guvernanța spațiului cibernetic in perioada cuprinsa intre trimestrul I al anului 2016 (n.a. data elaborarii studiului precedent), respectiv trimestrul I al anului 2017. Scopul urmarit de catre autor este de a „instituționaliza” in sfera academica un barometru multianual al securitații și guvernanței spațiului cibernetic românesc, care sa deserveasca evaluarii cantitative și calitative a implementarii politicilor publice ce privesc spațiul cibernetic autohton. English Abstract: Based on the studies I previously published, this paper aims to assess retrospectively the security and governance of the Romanian cyberspace in the period between the first quarter of the year 2016 (the time of the previous study) and the first quarter of year 2017. By publishing this series of studies I intend to institutionalize a multiannual barometer of the security and governance of the Romanian cyberspace, with the aim to periodically evaluate the Romanian public policies in cyberspace.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".