Bibliographic record
Abstract
L'auteur de cet article examine la relation existant entre les économies formelle et informelle, avec des apergus provenant de la recherche sur le Canada rural. L'économie informelle comprend la production, la distribution et la consommation de biens et services ayant une valeur économique, mais qui ne sont ni protégés par un code de loi formel ni enregistrés par des organismes de réglementation endossés par le gouvernement. Plusieurs allégations concernant l'interdépendance des deux économies sont formulées et testées en utilisant les données des Enquêtes sociales générates de 1992 et de 1998 sur l'emploi du temps. Les résultats confirment l'importance de l'economie informelle en tant que filet protecteur, tampon des changements structurels, constructeur de capacités et soutien de l'inclusion sociale. This paper discusses the relationship between the formal and the informal economies with insights derived from research on rural Canada. The informal economy is considered to be the production, distribution and consumption of goods and services that have economic value, but are neither protected by a formal code of law nor recorded for use by government-backed regulatory agencies. Several claims regarding the interdependence of both economies are developed and tested with time budget data from the 1992 and 1998 General Social Surveys. Findings support the importance of the informal economy as a safety net, buffer for structural changes, capacity builder, and support for social inclusion.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".