Postal Code Conversion File [Canada], July 1996, Census of Canada 1991
Bibliographic record
Abstract
The Postal Code Conversion File (PCCF) is a digital file which provides the correspondence between the six character code and Statistics Canada's standard geographical areas (e.g. Census divisions, Census subdivisions, Federal Electoral Districts) for which census data and other statistics are produced. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. The current version of the PCCF links over 787,000 postal code records, created up to the end of July 1996, to the geographical areas used in the 1991 Census and to Universal Transverse Mercator System (UTM) coordinates and latitude/longitude coordinates. This new version contains a new field called the single postal code indicator. This field will be useful in cases where a given postal code is assigned to multiple standard geographic areas. It indicates which of the standard geographic units is the most representative of the postal code. The purpose of the PCCF is to provide linkage capabilities that can be used for numerous applications, such as market research, demographic studies and geocoding applications. The file allows users to cross-reference geographic coordinates, census areas, and user-defined areas. For example, one of its key strengths lied in its capacity to integrate census data with user data. For more information on this product or some of its applications, please refer to the 'Products and Services Manual' or contact the Regional Geographer at one of our Regional Reference Centres across Canada. During the 1970s, there was an increasing demand for a large variety of statistics for small areas. To aggregate data by geographic areas, different types of address elements were examined manually, or by computer, in order to properly assign a geographical code. This assignment was complicated by the great variety of address formats on data files and spelling variations in street names. The introduction of the postal code in the mid-1970s has led to an entirely new approach. The postal code could be used as a structured representation of a range of mailing addresses. If the postal codes were matched to a standard geographic unit once, and the results retained in a lookup table, then the complex task of structuring and matching addresses could be avoided. Restricted File Access will be granted only to DLI and Odesi Subscribing Institutions.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.024 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.168 | 0.069 |
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".