General Social Survey, Cycle 24, 2010 [Canada]: Time-Stress and Well-Being, Episode File [version 5]
Bibliographic record
Abstract
This is the General Social Survey Cycle 24, 2010 Time-Stress and Well-Being Episode File Version 5. This survey monitors changes in time use, including time-stress and well-being. The two primary objectives of the General Social Survey are: a) To gather data on social trends in order to monitor changes in the living conditions and well-being of Canadians over time; and b) To provide immediate information on specific social policy issues of current or emerging interest. The purpose of this survey is to better understand how Canadians spent their time. Time use estimates can be produced based on information reported in the time use diary portion of the survey. This diary provides a detailed record of participation in a wide variety of daily activities, as well as the time devoted to them, where these activities took place, and the social relationships of the respondent. Also, for the first time, the 2010 GSS collected information on simultaneous activities, i.e. those that are performed at the same time as a primary activity. The questionnaire collected additional information on perceptions of time, time spent doing unpaid work, well-being, paid work and education, cultural and sports activities, transportation, and numerous socio economic characteristics.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.014 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.066 | 0.024 |
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".