Bibliographic record
Abstract
Abstract This article, by presenting a succession of images, proposes a retrospective look at the development of the field that studies consumption behaviour in the administrative sciences, managerial practices, and consumerism. These images or metaphors report on this re‐reading exercise of the field's history. More precisely, the presented reflection attempts to meet three objectives: (a) to propose a dynamic analysis of the chronological evolution of the field; (b) to produce a synthesis based on the rereading, according to the three above perspectives, respectively; (c) to contribute to the recognition of the diverse nature of the contemporary development of the field of marketing, from a pluralistic perspective. Résumé Cet article, sous la forme de l'exposition d'une succession d'images, propose un regard rétrospectif sur le développement du domaine de l'étude des comportements de consommation en sciences de l'administration, des pratiques managériales liées et du consumérisme. Ces images ou métaphores rendent compte de cet exercice de relecture de l'histoire du domaine. De façon plus particulière, la réflexion présentée se propose de répondre à trois objectifs principaux: (a) proposer une analyse dynamique de l'évolution chronologique du domaine, (b) dégager une synthèse à partir de la relecture faite, respectivement, selon les trois perspectives précédentes, (c) contribuer à la reconnaissance du caractère divers et multiple du développement contemporain du champ du marketing dans une optique pluraliste.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".