A Citizen’s Income would be institutionally feasible
Bibliographic record
Abstract
The question is this: given what we know about the ways in which social policies travel through the policy process, from idea to implementation, can we envisage ways in which a Citizen’s Income would be able to negotiate that journey? (‘Institutional feasibility’ is about the institutions of the policy-making process. Other writers call it ‘policy process feasibility’ or ‘strategic feasibility’.) Policy ideas reside in all kinds of places: books, the internet, think tanks, political parties, university departments, and government departments, to name but a few. To be implemented, ideas need to be able to travel through a complex institutional network, and particularly along the routes through think tanks, political parties, government departments, governments, and parliaments. Think tanks are particularly interesting as they enable political parties to hold internal debates without laying themselves open to accusations of disunity. The journey will be influenced by public opinion and by such self-interested players as computer companies; and certain policy characteristics might facilitate the journey, for instance, continuity with existing policy, and coherence with stated government priorities. Feasibility tests will usually need to be passed – but not always very thoroughly if a government wishes to implement a policy for political reasons. Electoral advantage will always be a factor. Sometimes a government or a think tank will carry out a pilot project. We have seen Citizen’s Income pilot projects in Namibia and India, but no true Citizen’s Income pilot in a developed economy. (Negative Income Tax experiments in Canada and the USA have provided us with useful information, but they were not Citizen’s Income pilot projects.) There is plenty of written material on Citizen’s Income schemes, and a global network of informed individuals is in place. Given the number of reasons for taking the Citizen’s Income idea seriously, detailed consideration by think tanks and government departments is not difficult to imagine. This could generate further media attention, and we can envisage sufficient numbers of ministers, shadow ministers, and members of parliament, in a variety of political parties, being persuaded that means-testing and other complexities have had their day and that an extension of universal benefits should be given a try. Public education would lead to sufficient public understanding, and this would provide the conditions for ministerial commitment and then legislation.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.023 | 0.007 |
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".