QQ The Canadian Consumer Tax Index tracks
Bibliographic record
Abstract
the total tax bill of the average Canadian family from 1961 to 2014. Including all types of taxes, that bill has increased by 1,886 % since 1961. QQ Taxes have grown much more rapidly than any other single expenditure for the average Canadian family: expenditures on shelter in-creased by 1,366%, clothing by 819%, and food by 561 % from 1961 to 2014. QQ The 1,886 % increase in the tax bill has also greatly outpaced the increase in the Con-sumer Price Index (697%), which measures the average price that consumers pay for food, shelter, clothing, transportation, health and personal care, education, and other items. QQ The average Canadian family now spends more of its income on taxes (42.1%) than it does on basic necessities such as food, shelter, and clothing combined (36.6%). By comparison, 33.5% of the average family’s income went to pay taxes in 1961 while 56.5 % went to basic necessities. QQ In 2014, the average Canadian family earned an income of $79,010 and paid total taxes equal-ing $33,272 (42.1%). In 1961, the average family had an income of $5,000 and paid a total tax bill of $1,675 (33.5%).
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.121 | 0.045 |
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".