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Record W2783480676 · doi:10.25904/1912/3856

Anticipatory Budgeting: A Long-Term Analysis of Old Age Pensions in Australia, Canada and Sweden

2005· dissertation· en· W2783480676 on OpenAlexaboutno aff
Alexander Gash

Bibliographic record

VenueGriffith Research Online (Griffith University, Queensland, Australia) · 2005
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
FundersDivision of Human Resource DevelopmentFörsäkringskassanSocialdepartementetEuropean CommissionMachine Tool Engineering FoundationAustralian GovernmentU.S. Department of the Treasury
KeywordsPensionPopulationPopulation ageingPoliticsDevelopment economicsRetirement ageSocial securityEconomicsPovertyPolitical sciencePublic economicsEconomic growthEconomic policyFinanceMarket economySociology

Abstract

fetched live from OpenAlex

The impact of population ageing on the social budgets of the future is a phenomenon confronting many of the world's wealthiest and most advanced nations. The impending retirement of the 'baby boomers' has raised concerns about the inadequacy of budgetary frameworks (both conceptual and real) to fulfil the financial commitments of demographically sensitive programs, namely old age pensions. Pension schemes represent, by far, the largest social welfare commitment of first world nations. Old age pensions are also demographically sensitive. Furthermore, pension systems play a crucial role in alleviating poverty, in recognising the previous contribution of an individual and in maintaining of the social and economic wellbeing of democratic polities. The financial stability of pension schemes and the ability of governments to meet future commitments will become significant issues of public policy as the pressures from population ageing intensify. Yet, committing resources, or budgeting, for longer-term pressures is an inherently problematic exercise both from an intellectual and a practical perspective. For long-term resourcing to be successful it requires perfect foresight and a level of political commitment that typically eludes most politicians and governments. Longer or medium-term budgetary pressures are often ignored or avoided until they impact on the immediate chances of either fiscal or electoral success. As such, societies face the prospect of looming financial burdens, but only have a box of short-term tools at their disposal and a limited body of scholarship to guide them through this ticking political 'time bomb'. This research tackles a significant omission in the existing literature on budgeting, public policy and social welfare, by proposing a conceptual framework for the anticipation, conceptualisation and analysis of future budget pressures. In doing so, it brings together analytical frameworks of government budgeting and social policy from a number of disciplinary areas and weaves them into a conceptual framework that allows for diagnostic and prescriptive analysis of budgetary pressures within a particular policy/spending area. The framework is also compatible with existing budgetary frameworks and decision-making processes. Through the analysis of the old age pension systems in Australia, Canada and Sweden this thesis makes an important contribution to the understanding of how demographic transition will impact on the future stability of pension schemes. The thesis contends that ageing populations will place significant pressure on each pillar of the pension system to meet its future financial commitments. This pressure will, in turn, have important implications for national budgetary processes and old age pension policy over the coming decades. In particular, governments will be required to implement a range of techniques that sit both within and beyond the traditional bounds of most budget processes. It will be imperative for researchers to explore the complexities and political possibilities of budget reform and to search for ways in which the longer-term needs of society can be adequately satisfied through the budget process.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.067
Threshold uncertainty score0.488

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.002
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 head0.139
GPT teacher head0.352
Teacher spread0.213 · 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

Citations2
Published2005
Admission routes1
Has abstractyes

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