Bibliographic record
Abstract
commodities, the amount of income we earn and the amount of free time we have left over after working to generate that income. Several time-use researchers and economists have emphasized the importance of free time when considering the quality of a person's life. Bittman & Matheson (1999) emphasized the importance of free time as follows; ‵‵The ability to participate in social life is the product of both access to leisure goods and services, and a sufficient quality of leisure Harvey (1996), a Canadian economist having lead the International Association for Time Use Research, concluded that ‵‵time poor people realize less household production, as the result of their time deficit, have to substitute these`missing' products and services by market products and services. A theoretical economics has examined the maximization of household utility between income preference and leisure time preference. It explains how households turn their income preference to leisure time preference based on the indifference curve. It is theoretically known that households turn their income preferences to leisure time preferences at some level of income. In this paper, we try to find empirically at what income level households change their preferences from income to leisure time. This is clearly different from concerns of such time use [Research Note]
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".