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Record W4323048119 · doi:10.1002/mar.21810

From warrior to guardian: An autoethnographic study of how consumers think about and interact with the natural world

2023· article· en· W4323048119 on OpenAlexaff
David R. Hannah, Caitlin Ferreira, Leyland Pitt

Bibliographic record

VenuePsychology and Marketing · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSensemakingEmbeddednessNatural (archaeology)Context (archaeology)NarrativePsychologySociologyEcologyMarketingPublic relationsBusinessGeographyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Abstract Consumers are increasingly concerned about how their interactions with the natural world affect both the health of that environment, and their own well‐being and enjoyment of life. More aware consumers seek to make sense of the natural world around them and consider how their consumer behavior impacts this environment. How actors notice and bracket ecologically material cues from a stream of experience and build connections and causal networks between these has been referred to as ecological sensemaking. This research examines ecological sensemaking in a specific context, that being in the experience of catch‐and‐release fishing. Data were gathered through a process of autoethnographic inquiry obtained over the course of four fishing trips. The results reflect the process of ecological sensemaking pertaining to the experience. Through the findings, we propose a new concept, ecological reasoning, which seeks to provide a critical link between ecological sensemaking and ecological embeddedness. Using this new concept, the research contributes to extant understanding of how consumers think about and interact with the natural world. Apart from constructing an overarching narrative of the experience, four subnarratives are also identified, in a chronological sequence that comprises the entire experience of catch‐and‐release fishing. The findings have implications for the broader management and marketing disciplines seeking to establish better ways of interacting with the natural world, both for themselves and their consumers.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.305
Teacher spread0.277 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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