Negotiated settlements and intergenerational equity in the pipeline service market: borrowing from Pete jr. to pay Paul sr.
Bibliographic record
Abstract
The movement from traditional regulatory hearings to negotiated settlements represents both a departure from cost of service regulation and a relaxation of regulatory oversight in the regulation of oil and gas pipeline tolls. Under negotiated settlements pipelines and shippers are able to renegotiate inclusions in their cost of service while simultaneously creating a profit margin for the pipeline where none existed under the cost of service outcome of a traditional hearing. Predicated on the observed preference of pipelines and shippers for negotiated settlements; most economic literature assumes that these settlements represent increased efficiency over hearings. Various claims have been made as to why negotiated settlements are more efficient than hearings but little attention is paid to other elements that affect these preferences without increasing efficiency. This thesis constructs a model to illustrate the existence of positive gains to pipeline and shipper from the re-allocation of expenses through time. This inter-temporal reallocation implies higher tolls for future shippers which is a concern for the National Energy Board (responsible for regulating Canadian oil and gas pipelines) as it places an unfair burden on future shippers and future end consumers of oil and gas. Behaviour consistent with the model is observable in anecdotal and econometric evidence provided in this thesis. Empirical investigation by Littlechild (2007) into settlement procedures in the Florida electricity market reveal similar findings; however, this analysis represents the first attempt to model the behaviour formally and provide econometric results. The econometric analysis uses new data collected and compiled specifically for this thesis.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 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".