Bibliographic record
Abstract
Everyone has a soft spot for pensioners. This probably explains most peoples’ unquestioning approval of pensioners’ travel concessions. However, it is argued here that concessions do not make sense because pensioners would be better off with the cash equivalent of their concessions. Concessions involve inefficiencies of which the following are the main ones.\n\nFirst, there are good arguments for some subsidies (e.g. health and education). These arguments do not apply well to pensioner travel. For example in the case of health, many people in the absence of the National Health Service would face sudden large bills for medical treatment. In contrast, the bill for essential travel, like going to the shops, is a predictable and modest weekly expense of the same order as the weekly cost of food ( for which pensioners are not given concessions ). \n\nSecond, about three quarters of the money spent on concessions is wasted in that it goes on transporting those who could afford the full fare or who are on non-essential journeys. In contrast, under a no concession scenario only about a quarter of the expenditure is wasted. Also, concessions are a poor means of supplying transport facilities to pensioners since about a third are not well served by public transport. In contrast, under a no concessions scenario, virtually all less well off pensioners get “transport subsidy money” since this money is contained in an increased state pension. Under a no concessions scenario, pensioners can spend their “subsidy money” on for example home delivery of groceries, taxi trips or subsidising relatives’ car running costs where the latter do the shopping. \n\nFourth, social exclusion is often used to justify concessions. It is shown that abolishing concessions, far from increasing social exclusion, might even reduce it.
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 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".