From Multiple Legal Cultures to One Legal Culture? Thinking About Culture, Tradition and Identity in European Private Law Development
Bibliographic record
Abstract
This paper begins by briefly outlining private law’s evolution alongside the emergence of the Nation States; it then aims to set out the mutual influence of these concepts on national culture, tradition and identity in order to highlight the significance of the political, economic and legal as well as social and cultural contexts in which the processes of integration and Europeanisation occur. Against this background, the scope for European private law to emerge as a plural, multi-level construct and a dynamic endeavour is recognised. Building on this analysis of the significance of the diversity and commonality of cultures, traditions and identities in national private law development, institutionalised at the Union level in the principle of unitas in diversitate, the paper explores the need for a single, common European notion of culture, tradition or identity. This examination is undertaken with reference to an example, namely the evolution of the concept of consumer, from its national foundations to its engagement in Union legislation and CJEU jurisprudence. Drawing conclusions as to the need for such a common, European concept, the paper advances a plea for the recognition of a shift in the perspective of legal development, to one which acknowledges the dynamic evolution of private law within a pluralist, multi-level regulatory construct.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.043 |
| Scholarly communication | 0.020 | 0.027 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".