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Record W3198154496 · doi:10.5267/j.ijdns.2021.7.004

The analysis of factors affecting the household savings as a part of food security management

2021· article· en· W3198154496 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Data and Network Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture Market Analysis Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsPurchasing powerFood securityBusinessGovernment (linguistics)Investment (military)PurchasingAgricultureEconomicsPublic economicsEconomic growthPoliticsMarketing

Abstract

fetched live from OpenAlex

Ensuring household food security should be a priority goal of state policy. The level of ensuring household food security reflects the state of the country's economic development and the effectiveness of agricultural policy. Household food security is achieved by ensuring a high level of purchasing power of households, which is possible by increasing income. Savings are the “safety cushion” for households during the financial and economic crisis caused by the coronavirus pandemic. The level of household savings is important both for the households themselves and for the country's economy, since savings, on the one hand, help to avoid hunger during crises, and, on the other hand, are an important investment resource for the country's economy. That is why assessing the level of household savings and identifying factors affecting savings are important aspects of building an effective government policy in the field of food security.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.260
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it