The Canadian Neighbourhood Early Childhood Development (CanNECD) Socioeconomic Index: Stability and Measurement Invariance Over Time.
Why this work is in the frame
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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.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it