Elementary-Secondary Education Statistics Project [Canada] [B2020 & Excel]
Bibliographic record
Abstract
The Elementary-Secondary Education Statistics Project (ESESP) is a national pilot survey that enables Statistics Canada to provide information on enrolments, graduates, educators and finance of Canadian elementary-secondary public educational institutions. This information is used mainly to meet policy and planning needs in the field of elementary-secondary education. ESESP annually collects aggregate data from each jurisdiction. Specifically, the information on enrolments pertains to the following four programs: regular, minority and second languages, Aboriginal language and special needs education. The information on regular programs is collected by type of programs (regular, upgrading and professional), education sector (youth or adult), grade and sex. The one on minority and second language programs is collected by type program (immersion, as language of instruction, as a subject taught) and by grade. Information on Aboriginal language programs is requested by type of Aboriginal language (immersion, as language of instruction, as a subject taught) and by grade. Finally, data on special needs education are collected by type of disability (sensory, physical and intellectual disabilities -- low incidence disabilities, learning disabilities and behavioural disabilities -- high incidence disabilities, to compensate for the socio-economic status (SES) or other disadvantages), type of class (regular, special) and by sex. The survey also collects data on secondary school graduates by type of program (regular, upgrading and professional), sector (youth and adult), age and sex. Graduation counts rates can be produced from this data. Information pertaining to full-time and part-time educators by age group and sex is also collected. Finally, ESESP also gathers expenditures data pertaining to level of government (school board and other government) and type of expenditures. This data is collected to determine how much is spent in relative detail by school boards and by provincial/territorial total. It also collects expenditures on special needs education programs. The information on elementary-secondary education statistics is used by provincial and territorial departments or ministries of education, national and provincial teachers' and students' associations, school boards, journalists and researchers, as well as international bodies such as OECD and UNESCO. ESESP was first introduced by Statistics Canada in 2003. The goal of this pilot project is to replace the following surveys as the official collection tools for elementary-secondary enrolments, graduates, educators and finance data: Elementary-Secondary School Enrolment Survey (ESSE -- Survey #3128), Minority and Second Language Education -- Elementary and Secondary Levels Survey (Survey #3129), Secondary School Graduates Survey (SSGS -- Survey #5082), Elementary-Secondary Education Staff Survey (ESESS -- Survey #3127) The ESESP has been replaced by the Elementary-Secondary Education Survey (ESES). Access data here
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.026 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.219 | 0.088 |
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".