Servicification of European manufacturing : evidence from Swedish micro level data
Bibliographic record
Abstract
European manufacturing seems to servicify - use and sell more services - but knowledge is poor. We illuminate the phenomenon using detailed and comprehensive micro level data at both the firm and enterprise group level for Sweden (1997-2006). We find that manufacturing is servicifying substantially. On the input side, services and qualified services are increasingly characterising in-house activity in manufacturing. On the output side, manufacturing's share of services sales in total sales is up as well as services exports. Moreover, we show that services sales are much greater (almost 60 percent higher) when all activities in manufacturing's enterprise groups are considered. This has not been shown for a European country before. It means that when we consider enterprise groups, the large discrepancy in manufacturing's services diversification between Canada and the EUcountries vanishes, at the least for Sweden. The results imply that treating services and manufacturing separately - e.g. in EU’s trade negotiations - may be out of date. Finally, the findings illustrate the value of enterprise group level data when studying structural economic changes.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".