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Record W2310611668 · doi:10.14288/1.0103549

How will the proposed Enbridge Northern Gateway pipeline affect the distribution of jobs nation-wide?

2012· article· en· W2310611668 on OpenAlexaboutno aff
Christine Ratcliffe

Bibliographic record

VenuecIRcle (University of British Columbia) · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsAffect (linguistics)Gateway (web page)Pipeline (software)Distribution (mathematics)Computer scienceBusinessWorld Wide WebPsychologyMathematicsCommunicationOperating system

Abstract

fetched live from OpenAlex

In this report I investigate how the proposed Enbridge Northern Gateway pipeline may affect the distribution of jobs nation-wide in Canada. The pipeline proposed, if built, will transport oil from the Albertan oil sands to the coast of BC at Kitimat. The nature of this study, which looks at Dutch Disease, means a focus on how job opportunities will shift industries and shift provinces from manufacturing in Eastern Canada to oil extraction in Alberta, Western Canada. In this report I will only briefly look at how jobs in Western Canada may be affected. The jobs in Western Canada are more positively affected by the proposed pipeline, however a large (pro)portion of these jobs are (jobs) expected to come about as an indirect result of the pipeline, rather than jobs directly created and therefore are difficult to calculate/take into consideration. Adding to the difficulty calculating the jobs creation, economies on the West coast are also threatened by oil spills. In Eastern Canada the effect on the job situation is a more abstract phenomena created through processes and characteristics in the economy. If the pipeline is built it will ship one kind of oil (bitumen) to markets in the Asia-pacific region. Being able to charge more for oil in Asia (Asia premium) may cause a real exchange appreciation in the Canadian dollar. One of the effects is positive as is it enables Canadians to buy more exports with their dollar. However this may be offset by the rise in the price of Canadian oil too and rise in cost of living. A second effect, and the concern that is related to Dutch Disease, is that the Canadian dollar changes in value. This change happens in such a way as to make goods that the Canadian manufacturing industry produces less competitive on a world market. This means that the demand for Canadian goods goes down; therefore, to keep the manufacturing industry going, jobs are cut. Some may point out that while this is the case jobs are being created in the booming sector – tar sands extraction in Alberta. This is the case but the geography of Canada, i.e. the size, makes it not possible for people to just swap industries without moving geographically. If the contraction of the Canadian manufacturing industry happens quickly not only will people not be able to move to the booming sector but additional economies, e.g. service sector economies, may not be able to grow quickly enough to fill the void the manufacturing industry left. In addition the politics of Canada, i.e. the structure of federal and provincial governments, complicates things still. In this report I look at how other countries have been able to mitigate Dutch Disease, the effect on the manufacturing industry, after discovering oil. However I find that Canada cannot simply do what these countries did because of the political structure. As a result I come to the conclusion that the Enbridge pipeline and any expansion of existing pipelines with a view to ship oil to the Asia- pacific market would be too great of a risk to the Canadian economy. If the tar sands are to expand and increase in output without ‘diversifying’ into the Asia-pacific markets there are a number of steps that can be taken to mitigate any negative economic impacts as outlined in the section headed ‘Curing Dutch Disease’. This report has only been able to explore a small part of the economic issues around tar sands expansion and associated pipelines. The issues go much further into other parts of the economy and environmental and social issues. The economic risks, some of which are explored in this paper need to be considered in conjunction with social and environmental risks for a true assessment of the cost-benefits that the tar sands and its pipelines will cause.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.010
GPT teacher head0.196
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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