Bibliographic record
Abstract
replacing the Manufacturers Sales Tax (MST) that had been in existence for about 70 years. The GST package included increases in sales tax credits which, the Finance Minister claimed, were designed to ensure that no family with an income of less than $30,000 per year would be worse off under the GST regime than they were with the MST. Almost a decade has past since the introduction of the GST. We are now in a position to evaluate the impact of the GST on Canadian families. Of particular interest is whether or not the Finance Minister’s guarantee holds. Have families at the bottom end of the income distribution, more specifically families with children, been disadvantaged by the GST. This study uses the Quadratic Almost Ideal Demand System (QUAIDS) (Banks, Blundell and Lewbel, 1997) and a series of Canadian family expenditure surveys (Famex) to investigate the impact of the GST on households, particularly those with children, in Canada. We calculate the change in welfare attributable to the introduction of the GST by estimating the expenditure change necessary to maintain pre-GST indirect utility. We compare the change in expenditure required to the change in transfers received to indicate whether households are better or worse off after the introduction of the “GST package. ” The analysis is preformed on households with and without children. We find that, although low-income single parent families fare well under the new tax regime, the majority of households including those with children are worse off. More specifically, of the households with incomes below $30,000 57%, 64 % of the households with children, were worse after the introduction of the GST. 31Some documentation refers to the Earned Income Supplement (EIS) as the Working Income Supplement (WIS). For continuity we will always refer to it as the Earned Income Supplement (EIS)
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.935 | 0.825 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".