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Record W4293553354 · doi:10.1177/01708406221124796

The Morality of Informality: Exploring binary oppositions in counterfeit markets

2022· article· en· W4293553354 on OpenAlexaff
Muhammad Abid, Joel Bothello, Shoaib Ul‐Haq, Alireza Ahmadsimab

Bibliographic record

VenueOrganization Studies · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsHEC MontréalConcordia University
Fundersnot available
KeywordsMoralityCounterfeitLegitimacyEmic and eticMoral economySociologySocial psychologyOpposition (politics)Positive economicsEconomicsPolitical sciencePsychologyLaw

Abstract

fetched live from OpenAlex

In seeking to explain the persistence of the informal economy – defined as the set of economic activities that are illegal yet legitimate to some large groups – scholars often focus on instrumental economic factors; in doing so, the role of morality is often overlooked. In response, we conduct a qualitative study of Pakistani counterfeit bazaars, to understand how market participants construct moral legitimacy in a way that justifies participation in, and thus contributes to sustaining, the informal economy. We reveal how the terms ‘counterfeit’ (representing the informal economy) and ‘authentic’ (representing the formal economy) function as an oppositional pair, both within the emic perspective of market participants but also within a baseline etic perspective of Western Intellectual Property regimes. Compared with this baseline, we find that market participants engage in three types of semantic transformation (invalidation, reframing and inversion) that shape moral assessments of authentic and counterfeit consumption. Through our study, we first contribute to a better understanding of how legitimacy in the informal economy is constructed. We also contribute to theory on ‘legitimacy as perception’, indicating how moral legitimization can occur through a dynamic of binary opposition between what is deemed to be ‘moral’ and ‘immoral’. Our final contribution is towards understanding how morality around counterfeit consumption is constructed.

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 score0.215
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.285
Teacher spread0.220 · 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

Citations13
Published2022
Admission routes1
Has abstractyes

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