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Record W6995558976

Partnership of convenience or opportunity for growth? : investigating the role of retailers in expanding local food schemes in the case study of EDEKA branches in northern Germany

2020· other· en· W6995558976 on OpenAlexaboutno aff

Bibliographic record

VenueEpsilon Archive for Student Projects (University of Southampton) · 2020
Typeother
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)General partnershipSupply chainFood supplyAgricultureGovernment (linguistics)Investment (military)Revenue
DOInot available

Abstract

fetched live from OpenAlex

In the past years growing interest in alternative forms of food supply chains has incentivised researchers to investigate the role of retailers in Short Food Supply Chains (SFSC) mainly in the United States, Canada and the EU, with little attention paid to SFSC retailer interaction in the German context specifically. The aim of this thesis to contribute to the existing literature by investigating how the country’s presumed institutional conditions affect the viability of selling via retailers for a certain type of SFSC producer. The location of the study was northern Hamburg, Germany. Six semi-structured interviews, substituted with four questionnaires, were conducted with micro- to large-scale producers involved in local SFSC schemes and selling via branches of the supermarket chain Edeka, and a group of producers who did not sell via this retailer. A document analysis of statements of producers and other stakeholders on the cities intention to support local agriculture by creating additional demand provided an overview of the effects of agricultural circumstances and policies had on SFSC. The interviews were analysed by applying Stevenson and Pirogs ‘values-based supply chain’ framework and showed that only micro- or mid- to large scale producers profited from the cooperation, which in the latter case was more of a partnership of convenience. In combination with the document analysis, which found limited land and capital access, expensive certification, as well as the need for more training in marketing and demand to impact local farmers, this conclusion indicates that additional outlets are not the only tools the city has to support local, especially small scale, agriculture.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.110
GPT teacher head0.348
Teacher spread0.238 · 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 designQualitative
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
Published2020
Admission routes1
Has abstractyes

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