MétaCan
Menu
Back to cohort
Record W7127041752 · doi:10.15407/socium2025.04.121

Corporate pension funds in Ukraine: features of formation and development prospects

2025· article· uk· W7127041752 on OpenAlex
Non-State Pension Funds 4/6, Omelianovycha-Pavlenka Str., Office 908, Kyiv, 01010, Ukraine, O. I. Makarenko

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUkrainian society · 2025
Typearticle
Languageuk
FieldEconomics, Econometrics and Finance
TopicLabor Market and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPensionAsset (computer security)Control (management)Investment (military)Asset managementGlobal assets under managementInstitutional investorNational PensionPersonal income

Abstract

fetched live from OpenAlex

The purpose of this article is to analyse and evaluate current trends in the development of corporate non-state pension funds, which over the last decade have become the main institutional element of the long-term savings system. Under the influence of demographic changes, increased labour mobility and reforms of state PAYG systems, corporate pension funds have become the main form of accumulative pension provision in many countries around the world. In global practice, they dominate in terms of asset volume and participant coverage in countries such as the Netherlands, the United States, the United Kingdom, Canada, and Australia. The main trend in the current development of corporate funds is the transition from defined benefit (DB) schemes to defined contribution (DC) schemes. This transformation is driven by the need to reduce financial risks for employers, increased life expectancy, and a shift in the philosophy of pension responsibility – from a guaranteed income model to a personal investment model. Under a DC scheme, employees enjoy greater transparency, mobility and individual control over their pension assets. Corporate pension funds are increasingly integrating modern digital asset management technologies. The use of automated investment strategies, digital identification, algorithmic risk monitoring and personalised pension planning platforms creates a new quality of interaction between the fund, the employer and the participant. This increases efficiency, reduces administrative costs and allows for the implementation of flexible pension solutions. In a broader context, such processes form the basis of a long-term savings model, in which the institutional stability of a corporate fund is combined with technological innovation, management transparency and personalised investment tools. The transformation of corporate pension systems, particularly in countries with high coverage, creates a powerful segment of institutional investors that plays a critical role in the development of financial markets and economic stability. These processes are extremely important for Ukraine. Given the low level of development of open pension funds, limited institutional investment, and low public confidence in financial institutions, it is the corporate sector that could become the starting point for a national accumulation system. One of the most realistic and quickest ways to launch it is to create corporate, non-state pension funds in large state-owned companies and infrastructure operators: Naftogaz of Ukraine, Ukrenergo, state-owned banks, Ukrposhta, Ukrzaliznytsia, etc. Such corporations have significant personnel structures, stable financial flows and an adequate level of state control, which ensures scalability, transparency and trust at the initial stage of reform. In addition, corporate pension programmes in the public sector can become the basis for the formation of long-term investment capital necessary for the restoration and modernisation of the Ukrainian economy after the war.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.293
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.230
Teacher spread0.199 · 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