Framing as a tool for analyzing European space policy
Bibliographic record
Abstract
Introduction The first two Galileo satellites were launched by a Russian Soyuz rocket from a base in French Guiana on 21 October 2011. This marked a crucial and long overdue step in the EU’s multi-billion euro investment in its own version of the US global positioning system. Galileo is expected to bring significant returns to the EU economy in the form of new businesses that can exploit precise spaceborne timing and location data. According to a press release published that day on the European Commission’s own website, the satellite navigation sector had already become ‘very important’ for the EU economy (contributing roughly 7 per cent of EU GDP in 2009) as well as for the ‘well-being of its citizens’ (see Europa website). It took three hours and forty-nine minutes for the satellite pair to reach their correct orbit 23,222 km above the earth. The BBC reported that European Communities Vice-President and Commissioner for Industry and Entrepreneurship, Antonio Tajani, said: ‘Galileo is at the heart of our new industrial policy. . . . We must commit very strongly to Galileo. We need this; this is not entertainment. This is necessary for the competitiveness of our European Union in the world.’ He then announced the industrial competition to procure six to eight more satellites over and above the 18 already contracted (Amos, 2011). The long overdue deployment phase of Galileo was the culmination of a lengthy process of framing and reframing the issue of satellite navigation and the question of whether Europe should pursue a collective space policy. A constellation of satellites is now planned for completion by 2019. The European Commission is currently promoting the message, based on independent studies, that Galileo will deliver around €90 billion to the EU economy in the first 20 years of operation ‘in the form of direct revenues for the space, receivers and applications industries’ and in ‘indirect revenues for society (more effective transport systems, more effective rescue operations, etc.)’ (see Europa website). Such an estimate may appear wholly ambitious for some in the space industry. Nonetheless, this ‘economy’ frame, which seeks to convey the benefits to ‘users’, ‘receivers’ and ‘industries’, is just the latest way of presenting the issue of satellite navigation as the prospect of fully exploiting the system draws closer.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".