Understanding Strategies in the Combinatorial Clock Auction: The Case of Canada's 700 MHz Auction
Bibliographic record
Abstract
Industry Canada, the authority charged with radio spectrum allocation and assignment in Canada, administered a Combinatorial Clock Auction in 2014 whereby a sizable number of spectrum licenses were awarded to a handful of telecommunications operators to provide 4G cellular service throughout the Canadian provinces.The auction format, the Combinatorial Clock Auction (CCA), is now increasingly replacing the Simultaneous Multiple Round Auction (SMRA) as the preferred method to assign commercial radio spectrum. The CCA has been used in several countries by spectrum authorities to assign spectrum bands for cellular (4G) services and wireless broadband.In its essential design the Canadian CCA consists of two main stages: the Allocation stage and the Assignment stage; in turn the allocation stage is further divided in two: the Clock Rounds and the Supplementary Round. This paper discusses the main features of the CCA and highlights some of the differences with other previously used formats. Next, it uses an extensive repository of data from the results of Canada’s 700 MHz auction in order to analyse the strategic aspects of auction participants' bids occurred during the first stage of the auction, known as the Clock Rounds. Data is publicly available, posted by Industry Canada, and traces every bidder’s demand history throughout the auction represented by the round-to-round demanded bundles and the aggregate bid (bid price) for each bundle. Bidding data also shows a bidder's eligibility and activity levels, two important auction measurements of activity that constrain a bidder's behaviour.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".