Collective Certification in UK Competition Law: Commonality, Costs and Funding
Bibliographic record
Abstract
The UK introduced a new regime for opt-out ‘class’ or collective actions in 2015. These require certification before they proceed to trial to establish whether the members of the class have sufficient ‘common interest’. The certification of the first two collective actions – Gibson v. Pride Mobility Products and Merricks v. Mastercard – were dismissed by the Competition Appeal Tribunal (CAT). Here a critical assessment of the UK’s emerging collective certification process is undertaken focusing on the determination of common issues, pass on, distribution of damages, costs and funding. It is argued that the CAT has applied the test for certification too strictly and not in accordance with the case law surrounding the ‘Canadian model’ on which the UK certification procedure is based; and incorrectly treated the award of aggregate damages as the summation of individual damages. The way the CAT has handled these two factors threatens to undermine the purpose and effectiveness of the UK’s new collective action regime.
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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 | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.020 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.016 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".