The Canadian Neighbourhood Early Childhood Development (CanNECD) Socioeconomic Index: Stability and Measurement Invariance Over Time.
Bibliographic record
Abstract
Objectives and ApproachThe CanNECD SES Index is a composite of 10 Canadian Census and Income Tax Filer variables, aggregated to 2,038 custom neighbourhoods covering all of Canada. The baseline 2006 Index accounted for 32% of the neighbourhood-level variance in overall developmental vulnerability in Kindergarten children, as measured by the Early Development Instrument (EDI). Other existing SES indices accounted for 17% at most. The Index now has two additional time points (2011 and 2016), which allows an evaluation of its consistency over time. Our objective is to assess three aspects of the Index’s temporal consistency. The first is the consistency of the strength of association between the Index and vulnerability rates across EDI developmental domains. The second is the consistency of neighbourhoods’ quintile rank over time. Finally, we use Confirmatory Factor Analysis in an SEM framework to assess the Index’s measurement invariance over time. ResultsFor each EDI domain, the strength of association between Index scores and neighbourhood-level vulnerability rates were either maintained or minimally declined over time. Additionally, neighbourhood quintile rankings were highly consistent over time with over 60% of neighbourhoods in the same quintile between 2006 and 2016, and fewer than 3% with a greater than one-quintile change. Finally, our preliminary measurement invariance results show at least configural invariance over the three time points. Conclusion / implicationsOur results confirm the stability of the CanNECD Index, justifying its utility for: mapping SES indicators across neighbourhoods and over time, contextualizing neighbourhood-level developmental vulnerability in young children, and identifying interesting neighbourhoods for future study, especially those where the children are faring much better than predicted by the Index.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".