MétaCan
Menu
Back to cohort
Record W2747781041

New and Improved: How to Bring Institutional Investment into Public Infrastructure

2017· article· en· W2747781041 on OpenAlexaboutno aff
Benjamin Dachis

Bibliographic record

VenueC.D. Howe Institute Commentary · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsFinanceBusinessPensionGovernment (linguistics)RevenuePublic infrastructureInstitutional investorCritical infrastructureInvestment (military)Corporate governancePolitics
DOInot available

Abstract

fetched live from OpenAlex

Canadian governments are on the verge of the largest infrastructure spending increases in decades. The challenge for policymakers at all levels of governments is to decide whether they should seek more private funding. Canadian institutional investors – notably the seven largest Canadian public pension plans as well as global investors – are looking to participate in new user-fee-supported infrastructure: both in existing assets and in new projects. To provide Canadian retirees with the best possible returns, Canada’s largest pension plans have invested $87 billion of their $1 trillion-plus in assets in infrastructure, but mostly abroad. Meanwhile, Canadian and foreign institutional investors such as pension funds and insurance companies would likely place a high value on Canadian user-fee financed infrastructure, but Canadian governments have opened few opportunities for such investment. Indeed, this Commentary argues that government ownership of infrastructure has led to inefficient management, poor project selection, and higher risks on taxpayers disguised by low government borrowing costs. To provide opportunities for investors to meet beneficiaries’ needs through financing infrastructure, Canadian governments should create policies that support institutional investment in both existing assets and for new infrastructure. Existing government-owned, user-fee-financed assets offer the greatest potential for government revenue from asset sales, including partial sales in which governments retain economic control. Governments could use the proceeds from such institutional investment to fund new infrastructure – particularly social-service infrastructure like schools and hospitals and other non-fully-self-financing infrastructure – alongside institutional investors. Taxpayers would benefit from better use of existing assets, as would users of more efficient infrastructure. The federal government recently announced plans to create an infrastructure bank that it would initially bankroll, but with a mandate to foster institutional investment capital for new public infrastructure. It is critical that Ottawa get right the design details of such a bank as well as other related institutions. There are differences between private investment in new versus existing infrastructure. But many policy issues are the same. In addition to an infrastructure bank, Canadian governments should take the following steps to encourage more institutional infrastructure investment: • where necessary, create independent regulatory bodies to oversee infrastructure assets that ensure their owners, either government-owned corporations or institutional investors, act in the public interest ahead of private profit and for long-term sustainability; • open infrastructure investment opportunities to the highest bidder among domestic or foreign investors and do not require any provincial or federal pension funds to invest. This requires the federal government to have expertise it can lend to smaller communities on business cases for institutional investors; • seek out opportunities to “recycle” user-fee financed assets at their maximum value to taxpayers or allocate contracts to operate new non-full-user fee assets that provide the highest savings or cost-avoidance; and • provide financial encouragement to provincial and municipal governments to work with the federal infrastructure bank since they own the vast majority of existing and potential user-fee financed infrastructure of interest to institutional investors.

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)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.884
Threshold uncertainty score0.839

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0170.018
Scholarly communication0.0190.014
Open science0.0040.005
Research integrity0.0100.011
Insufficient payload (model declined to judge)0.0230.004

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 head0.026
GPT teacher head0.290
Teacher spread0.264 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueC.D. Howe Institute CommentarySame topicCanadian Policy and GovernanceFrench-language works237,207