Assessing European national policies to support the competitiveness of information and communication technology producers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose In the context of fears that the European information and communication technology (ICT) sector may be facing a period of crisis, this paper seeks to examine the changing role of national‐level policy initiatives to enhance the competitiveness of European ICT producers. Design/methodology/approach The article is based upon a study of 176 national programs that are aimed specifically or in substantial part at ICT producer goods. This supply‐side focus provides a counterpoint to studies that concentrate on demand stimulation and aggregation measures, which generally make up a much larger share of national policy programs. A comparative analytical framework is used that takes account of the different composition and structure of the ICT industries in the EU member states. Findings The key findings are that technology development programs continue to dominate but that the emphasis is shifting from ICT producer goods as such to the application and coordination of ICT products and services across a wide range of industry contexts. This process takes different directions depending upon national political and administrative structures and historical national attitudes to industry policy. Originality/value The article gives evidence about sector specific strategies for supporting the competitiveness of the ICT sector and forms the basis for the identification of best practice examples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it