MétaCan
Menu
Back to cohort
Record W2270265451

Why Stewardship is Proving Elusive for Institutional Investors

2010· article· en· W2270265451 on OpenAlexaboutno aff
Simon C. Y. Wong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutional investorBusinessFiduciaryShareholderPortfolioStewardship (theology)Corporate governanceFinanceCustodiansDiversification (marketing strategy)AccountingAsset managementAsset (computer security)Duty
DOInot available

Abstract

fetched live from OpenAlex

As the dominant owners of listed companies in many developed markets, institutional investors have been under increasing pressure to act as responsible shareholders. In the UK, Canada, France, the Netherlands, and other markets, stewardship codes have been developed or are under consideration to encourage pension funds, insurance companies, and their asset managers to monitor and engage investee companies actively with the view to protect and enhance shareholder value.However, attempts in recent decades to convince institutional investors to act as active, long-term oriented “stewards” have fallen short. This is because modern investment management practices and characteristics – such as financial arrangements that promote trading, excessive portfolio diversification, lengthening share ownership chain, misguided interpretation of fiduciary duty, and flawed business model and governance approach of passive funds – make genuine stewardship challenging for institutional investors.Although these deficiencies are extremely serious, they may be remedied through a combination of actions, including by eliminating unnecessary intermediation, developing in-house investment management capabilities, revamping performance metrics, and rationalizing portfolio holdings.While not all investors need to be stewards and stewardship obligations should be allowed to be discharged in different ways, tackling the underlying structural impediments will make it easier – and more natural – for asset owners and asset managers to adopt an active, long-term oriented mindset.

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)0.014
metaresearch head score (Gemma)0.037
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.021
Scholarly communication0.0120.015
Open science0.0010.006
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.219
Teacher spread0.202 · 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
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

Citations51
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicState Capitalism and Financial GovernanceFrench-language works237,207