Getting Citizens to Save: Media Influence on Incentive-Based Policies
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.
Bibliographic record
Abstract
Abstract Governments often introduce financial incentives to citizens in order to encourage ‘personally responsible’ behaviour. Examples of these types of incentives include tax-deferral or tax-free incentives around retirement savings. These types of incentives are shown to matter to investment strategies in the aggregate, but we still lack a full explanation as to how individuals respond to these types of incentives, and what role media play in advertising these incentives. This paper illustrates the potentially vital role that media play in enhancing contributions to one incentive-based policy, the Registered Retirement Savings Plan (RRSP) in Canada (2000–2013), using aggregate contribution data, media data, as well as individual-level survey data from the Canadian Financial Capability Survey. Results show that media advertising of the programme influences contribution outcomes and, while media may not outweigh lifecycle effects such as proximity to retirement, it is nonetheless an essential – and overlooked – motivator for contributions to late-life savings.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it