Moment of reckoning for household food insecurity monitoring in Canada
Bibliographic record
Abstract
Tweet this articleHousehold food insecurity, inadequate or insecure access to food due to financial constraints, is a serious population health problem in Canada, linked to poorer men tal health, 14 higher rates of infectious 5 and noncommunicable diseases 6,7 and inju ries, 8 increased health care utilization, 912 and premature mortality.13 Monitored since 2005 with the wellvalidated Household Food Security Survey Module (HFSSM) on the Canadian Community Health Survey (CCHS), 14 this problem was widespread and growing before the pandemic.15,16 It affected 12.7% of households, about 4 370 000 people, in 2017 to 2018.15 Recog nition of the need for more effective responses was evident in two major fed eral policy initiatives.The Poverty Reduction Strategy, released in 2018, identified the prevalence of household food insecurity as a valuable indicator of Canadians' abil ity to meet basic needs, 17 prompting the addition of the HFSSM to the Canadian Income Survey (CIS) to facilitate annual reporting on the Poverty Dashboard, a website introduced to track the Strategy's key poverty indicators.18 In 2019, house hold food insecurity was identified as a priority in the Food Policy for Canada.19 Concerns about food insecurity became heightened in the spring of 2020 as pandemic related business closures forced thousands out of work.20 In addition to rapidly implementing new income sup port and wage subsidy programs, federal and provincial governments introduced massive new funding programs for food banks and other charitable food assistance programs.2124 Population surveys were temporarily suspended, but in May 2020, an abbreviated measure of food insecurity was included on the Canadian
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".