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Record W3172406618

Food wastage reduction

2021· article· en· W3172406618 on OpenAlexaff
Reshma A. Babu, G. Kavya, B R Harshitha

Bibliographic record

VenueInternational journal of advance research, ideas and innovations in technology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsSustainabilityFood wasteBusinessCleaner productionFood industryFood processingMarketingEnvironmental economicsWaste managementEngineeringEconomicsMunicipal solid wastePolitical science
DOInot available

Abstract

fetched live from OpenAlex

There is growing evidence that a significant share of global food is thrown away, with concomitant detrimental repercussions for sustainability. Reducing food waste is a key sustainability challenge for the foodservice industry. Despite the significance of this issue to the global foodservice industry, the link between innovation practices and food waste management has received limited attention in the academic literature. This paper uses innovation management and social constructionism to investigate the interrelationships of foodservice provisions and innovations in waste management. It is based on the evaluation of food waste solutions and innovations that combine strategic dimensions of waste management with practice-driven initiatives, including incremental (processes and technologies) and radical innovations. The paper presents a range of waste management initiatives, showing that their implementation in the foodservice sector varies depending on management’s beliefs, knowledge, goals, and actions. The concepts discussed here could help practitioners to become more aware of the factors that drive the adoption of food waste innovations. The prevalence of food waste has been a subject of interest and discussion in recent years and researches is being done to find effective ways to curb it. It has been identified as a primary issue in the sustainability of food production and consumption, in addition to the sustainability of food supply chains. Food waste can be divided into avoidable and unavoidable waste. Avoidable waste includes edible food and spoiled/damaged edible food, while unavoidable waste consists of inedible food like bones, fruit peels, and eggshells among others. Research shows that in Finland, 5% of purchased food is wasted in households, and an average person wasted about 20-30 kg of food in a year. The average total amount of food wasted in households yearly is about 120-160 million kilograms. Household wastage could be intentional or not. Many of the food wastage in households could be a result of forgetfulness or negligence for the food expiry date. In countries like Finland with the high cost of living, consumers are inclined to buy food nearing its expiry date due to the discount shop sellers attach periodically.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.202

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
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 head0.030
GPT teacher head0.346
Teacher spread0.316 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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