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Record W2897916604 · doi:10.1111/issr.12175

Introduction: Quantifying and reporting social security obligations

2018· article· en· W2897916604 on OpenAlex
Assia Billig, Simon Brimblecombe, Jean‐Claude Ménard

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Social Security Review · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsActua
Fundersnot available
KeywordsTransparency (behavior)Social securityEquity (law)PensionWork (physics)Context (archaeology)Public economicsPolitical scienceBusinessEconomicsFinanceEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract In a context of increasing transparency of social security scheme design and financing, assessing the financial implications of the promises made to current and future retirees of a social security pension system has become a key issue. The central role played by actuaries in the financial evaluation of social security systems means that the debate regarding methods and assumptions to use in such an exercise is of interest to all actuaries, those who use their work and those whose decisions are based on their work. This, in theory, appears a rather technical debate. However, in reality, these deliberations have a much wider impact. The discussion around how to assess the implications of promises made by social security systems to current and future populations will affect the decisions taken regarding the key features of systems, in particular the social contract between generations. It also feeds into the debate regarding sustainability, inter‐ and intra‐generational equity, the adequacy of benefits and the robustness of systems; that is, how future changes to the economic and demographic environment will affect systems. This introductory article discusses the importance of this topic including the implications for actuaries, policy‐makers and other stakeholders and then summarizes the six substantive articles that comprise this special issue. These articles reflect different points of view, but also different experiences and environments – which adds to their value as contributions to this important debate. Finally, this introduction sets the context for the reader – to ensure that the technical aspects of the set of papers are considered within the wider framework of social security provision and financing.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.061
GPT teacher head0.345
Teacher spread0.284 · 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