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Record W2943906922 · doi:10.24043/isj.83

CSR as a strategy for public-private relationships in protected island territories: Fuerteventura, Canary Islands

2019· article· en· W2943906922 on OpenAlexvenueno aff
Olga González‐Morales

Bibliographic record

VenueIsland Studies Journal · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsnot available
Fundersnot available
KeywordsGeographySmall islandBusinessRegional scienceEconomic geography

Abstract

fetched live from OpenAlex

This article reflects on governance and Corporate Social Responsibility (CSR) as a competitive strategy. It shows that synergies for achieving sustainable tourism destinations require innovation, inter-business cooperation, and public-private cooperation. The empirical analysis focuses on the island of Fuerteventura, Canary Islands. The island is an outermost territory of the European Union, where the high number of tourists has an important socio-environmental impact. Fuerteventura has also been designated a Biosphere Reserve due to respect for its cultural, natural and scenic values and the manner in which commitment to renewable energy, responsible water management and responsible fishing have contributed to its sustainable development. This recognition has led to a coordinated decision-making process, which has resulted in the implementation of different plans to modernize this tourist destination. In fact, the island has been divided into three basic zones that differ in the conservation levels pursued and the activities allowed in each of them. In this context, this article aims to analyze the influence of innovation, private-public collaboration and private-private collaboration on tourist accommodation companies regarding their level of integration of CSR in an island designated as a Biosphere Reserve

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.126
GPT teacher head0.299
Teacher spread0.174 · 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 designObservational
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

Citations8
Published2019
Admission routes1
Has abstractyes

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