Residential Telephone Service Survey December, 2004 [Canada]
Bibliographic record
Abstract
A sample of approximately 42,000 respondents is used for this survey (five out of six rotation groups). The survey data are collected using Computer Assisted Interviewing (CAI). The first data collection procedure took place during Novembers LFS week in 1996. This microdata file is prepared biannually and contains the variables from the survey, plus geographical variables from the LFS (province, census metropolitan area, urban/rural breakdown). No other variables from the LFS are added to the file. Concern had been expressed in 1996 that the mechanism for monitoring penetration rates was not adequate in providing timely results to indicate whether Canadian penetration rates fall as a result of increases in local rates. At that time, data on penetration rates were available from the Household Facilities and Equipment Survey (HFE) but only on an annual basis. Given the changes that were and will be occurring in the basic residential telephone rates, an annual survey was not adequate to accurately reflect the impact that these changes are having on Canadian telephone subscribership. The latest Residential Telephone Service Survey (RTSS) was conducted by Statistics Canada in December 2004 with the cooperation and support of Bell Canada. There are two main objectives which Bell Canada has outlined. They are: (I) to collect information on penetration rates across Canada (and make them available by province); (ii) to collect information on non-subscriber 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.022 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.021 |
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".