Introduction: Quantifying and reporting social security obligations
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".