COVID-19 and the Economic Importance\nof In-Person K–12 Schooling
Bibliographic record
Abstract
La mesure dans laquelle il conviendrait de garder ouverts les établissements d'enseignement de la maternelle à la 12e année est au premier plan des discussions liées à la gestion à long terme de la pandémie. Dans ce contexte, l'importance immédiate de l'éducation de la maternelle à la 12e année pour le reste de l'économie n'a été que timidement évoquée. La suppression de l'enseignement en classe réduit le temps dont disposent les parents d'enfants d'âge scolaire pour travailler, ce qui a pour effet de réduire le revenu versé à ces travailleurs et d'affaiblir l'économie dans son ensemble. Nous traitons de deux indicateurs de cette importance économique et de la façon dont ces indicateurs peuvent être modifiés de manière à mieux refléter le rôle déterminant que joue l'éducation de la maternelle à la 12e année. Le premier indicateur est la taille du secteur, représentée par la fraction du produit intérieur brut qu'il engendre. Le second est la centralité du secteur, soit la mesure dans laquelle il est essentiel au réseau d'activité économique. À l'aide de données tirées du recensement de la population du Canada et des tableaux d'entrées-sorties symétriques, nous démontrons que la prise en compte de ce rôle crucial accroît considérablement l'importance de l'éducation de la maternelle à la 12e année. Abstract: The extent to which elementary and secondary (K–12) schools should remain open is at the forefront of discussions on long-term pandemic management. In this context, little mention has been made of the immediate importance of K–12 schooling for the rest of the economy. Eliminating in-person schooling reduces the amount of time parents of school-aged children have available to work and therefore reduces income to those workers and the economy as a whole. We discuss two measures of economic importance and how they can be modified to better reflect the vital role played by K–12 education. The first is its size, as captured by the fraction of gross domestic product produced by that sector. The second is its centrality, reflecting how essential the sector is to the network of economic activity. Using data from Canada's Census of Population and Symmetric Input–Output Tables, we show how accounting for this role dramatically increases the importance of K–12 schooling.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.003 |
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".