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Record W7135449258

Analysis of the pension systems of selected countries

2013· dissertation· cs· W7135449258 on OpenAlexaboutno aff
Jakub Málek

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2013
Typedissertation
Languagecs
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPensionPension systemSustainabilityConsumption (sociology)Pension insurance
DOInot available

Abstract

fetched live from OpenAlex

The topic of this thesis is the issue of pension systems, which are an integral part of every advanced society. The aim of this thesis is to provide an insight into the basics of the issue, analyze selected pension systems and to assess the possibility of introduction similar pension systems in other countries. In the theoretical part of the thesis first presents basic aspects of the development of approach to finance consumption in old age, possible forms of pension systems, the risks that are associated with them, as well as several models of pension system that are currently enforced. In the analytical part pension systems of Australia, Denmark, Canada, Netherlands, Sweden and Switzerland are first specified separately and subsequently, on the basis of criteria coverage rate, financial sustainability and adequacy of pensions, subjected to comparative analysis. The result of the analysis is the determination of the Dutch pension system as a system that has, although not in all analyzed areas, the relatively best results of functioning. However, the widespread introduction of this system definitely not recommended, due to given economic differences in various countries, which are described in the conclusion of this thesis. Nevertheless of each pension system we can choose a positive approaches to solving problems on which we can build in the future.

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)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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