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Record W1984681691 · doi:10.1504/gber.2009.025382

A strategic matrix model for the apple industry in Lebanon

2009· article· en· W1984681691 on OpenAlex
Rock-Antoine Mehanna

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueGlobal Business and Economics Review · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsRivalryGovernment (linguistics)SubsidyPrivate sectorValue (mathematics)Business modelPublic sectorStrategic planningBusinessIndustrial organizationEconomicsMarketingEconomyEconomic growthMarket economyComputer scienceMicroeconomics

Abstract

fetched live from OpenAlex

The purpose of this study is to examine the Lebanese apple industry from a strategic macromanagement perspective. It employs the Industry Value Chain (IVC) framework, along with Porter's Five Forces of rivalry as a methodology to enable the formulation of a matrix model comprising grand and competitive strategies. Several experiences from the USA, New Zealand, Chile, Mexico and Canada are discussed to draw some differences and similarities. This topic comes at a time when the government is struggling to find solutions for the apple sector. However, the governmental discussions and suggested solutions pivot mostly around technical and policy-oriented issues (e.g., government subsidies and limited seasonal national campaigns), disregarding any serious analysis of business-oriented solutions and private-public sector collaboration.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.034
GPT teacher head0.244
Teacher spread0.210 · 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