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Record W1975819771 · doi:10.1080/01490400802017464

A More Tenable Marketing for Leisure Services and Studies

2008· article· en· W1975819771 on OpenAlexaff
Andrew T. Kaczynski

Bibliographic record

VenueLeisure Sciences · 2008
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMarketingSkepticismMarketing researchMandateServices marketingPerspective (graphical)Public relationsRelationship marketingPublic Sector MarketingContext (archaeology)Return on marketing investmentSocial marketingConfusionSociologyMarketing managementBusinessMarketing sciencePsychologyPolitical scienceService (business)EpistemologyLawComputer science

Abstract

fetched live from OpenAlex

The integration of marketing principles and practices into leisure services and studies over the past 25 years has been met with significant confusion and skepticism. Recent theoretical re-conceptualizations of public leisure services marketing suggest that a new marketing philosophy is needed to guide marketing efforts in this context. This paper argues that social marketing, previously largely ignored in the leisure literature, offers a perspective more consistent with the mandate of public leisure services. An explicit goal of the essay is to clarify confusion surrounding marketing and to describe a more tenable philosophy so that a wider range of subdisciplines in leisure services and studies might take advantage of some or all of the beneficial aspects of marketing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0080.052
Scholarly communication0.0240.024
Open science0.0020.009
Research integrity0.0110.022
Insufficient payload (model declined to judge)0.0090.002

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 head0.075
GPT teacher head0.368
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), 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

Citations35
Published2008
Admission routes1
Has abstractyes

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