The $200 Million/Year Price Tag For Superannuation Fund Governance: A Case Study of Fund Member Loss
Bibliographic record
Abstract
As the 21st century began in Australia, 91 % of all Australians were covered by superannuation. In turn, total superannuation assets had reached $960 billion by the first quarter of 2006 with balances in superannuation funds now the largest financial asset held by households. This substantial growth in superannuation coverage did not, however, occur as a result of free market forces operating between producers and consumers in the superannuation industry. Rather, this increase can be directly traced to the level of intervention in the industry by both the Labor and Coalition Governments throughout the 1980s and 1990s. This pattern has again been replicated in the 21st century with a ‘trilogy ” of major superannuation reforms occurring in the period from 2001 to 2006 including the 2004 Registrable Superannuation Entity licensing (RSE) regime. However, in spite of the public interest rationale provided by both governments, these regulatory reforms have failed to achieve recognition as a vehicle for advancing the welfare of Australian workers in their role as superannuants or for improving the welfare of the nation. Rather, criticisms relating to interest group lobbying for private gains continue to grow unabated. At the centre of this controversy are two key issues: 1) while fund member benefits from these reforms are limited, the associated compliance costs of fund governance, which are deducted from fund member returns, approached $200 million per year in 2006; and 2) the primary winners of the regulatory interventions, in terms of, for example, improved return-on-asset figures, appear to be the industry fund managers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".