Estimating Population Counts for Dissemination Areas and Census Tracts in Canada from 2011 to 2021
Notice bibliographique
Résumé
Abstract Accurate small-area population estimates are essential for health research and social policy development. While Statistics Canada provides census-year population counts for all geographic units, it does not produce intercensal estimates for Dissemination Areas (DA) and Census Tracts (CT). This study addresses this gap by estimating DA- and CT-level population counts for 2011 to 2021 using census data and interpolation techniques. Population counts were derived from Statistics Canada’s Geographic Attribute Files for 2011, 2016, and 2021. We applied linear interpolation to estimate intercensal population counts (2012–2015 and 2017–2020). We used an areal-weighted interpolation technique to account for boundary shifts due to census geography changes, utilizing Statistics Canada’s Correspondence Files. The final datasets provide consistent population estimates across census cycles, enabling longitudinal and neighbourhood-level analyses. The methodology and accompanying R script, available as supplementary materials, can be adapted for other intercensal periods and other demographic information, promoting transparency and reproducibility in demographic research. This study facilitates data-driven decision-making in public health and policy development by providing a reliable and scalable methodology for estimating intercensal population counts. About the Research Department The Saskatchewan Health Authority Research Department leads collaborative research to enhance Saskatchewan’s health and healthcare. We provide diverse research services to SHA staff, clinicians, and team members, including surveys, study design, database development, statistical analysis, and assistance with research funding. We also spearhead our own research programs to strengthen research and analytic capability and learning within Saskatchewan’s health system. Disclaimer This working paper is for discussion and comment purposes. It has not been peer-reviewed nor been subject to review by Research Department staff or executives. Any opinions expressed in this paper are those of the author(s) and not those of the Saskatchewan Health Authority. Suggested Citation Marouzi Anousheh, Plante Charles. 2025. “Estimating Population Counts for Dissemination Area and Census Tracts in Canada from 2011 to 2021.” MedRxiv. Author Contributions AM conducted the data analysis and prepared the first draft of the article. AM and CP designed the study and directed its implementation, including quality assurance and control. CP supervised the data analysis. CP reviewed, edited, and finalized the text. CP provided the overall guidance and funding for the research project. All authors approved the final version of the manuscript. Funding Statement This research was funded by the Saskatchewan Health Research Foundation (SHRF). Ethics Declaration This study exclusively utilizes publicly available, de-identified population data obtained from Statistics Canada. No human participants, personal identifiers, or confidential information were involved in this research, and therefore, ethical approval was not required. Conflict of Interest The authors declare that they have no conflict of interest. Data Availability All data used in this study is for public use and can be accessed through the Statistics Canada website. Code Availability Codes are available as a supplementary file to this working paper.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,010 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».