The Kijiji Second-hand Economy Index: 2016
Bibliographic record
Abstract
In 2015, the Kijiji Second-Hand Economy Index launched to more closely examine the growing phenomenon that is the second-hand economy The intention of the inaugural study was to devise a first-of-its-kind annual Index to measure Canadians’ second-hand practices and their impact on the Canadian economy As with the 2015 Index, this year’s study measures the growth and intensity of the second-hand market over the last 12 months by taking a closer look at the process of acquiring and disposing of used goods (cf intensity index of second-hand practices) The study expanded this year to include additional data from major Canadian cities, as well as gather some interesting insights on Canadians’ purchasing intentions and experiences in the second-hand marketplace.This study also reviews the growing significance of the second-hand economy, the interaction between it and the new-goods market place and the resulting contribution to economic activity and consumer well-being. Raising awareness of the economic benefits of this sector and its benefits to Canadians may lead to more participation, thereby reinforcing and growing its benefits. Further, highlighting its contribution to the economy, we hope to pave the way to advancing policy formation in this sector
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".