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Record W2317638116 · doi:10.1177/0973005215599280

Market Separations for BOP Producers

2015· article· en· W2317638116 on OpenAlexfundno aff
Ramendra Singh, Sharad Agarwal, Pratik Modi

Bibliographic record

VenueInternational Journal of Rural Management · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsBusinessDomestic marketIndustrial organizationBottom of the pyramidMarket segmentationSeparation (statistics)Factor marketMarket developmentMarket microstructureMarket shareMarketingMarket economyEconomicsOrder (exchange)International tradeFinance

Abstract

fetched live from OpenAlex

In this article, we study the Chanderi handloom cluster as a case of market development by applying and extending Bartels’ (1968) theory of market separations. We conduct 12 in-depth semi-structured interviews of various stakeholders involved in the process of market development and validate four market separations suggested by Bartels. Additionally, we also find evidence of a new (fifth) market separation, which we label as ‘social market separation’. We empirically argue that social separation is an equally important market separation that inhibits market development at the Bottom of Pyramid (BOP), often acting as a barrier to market development. It may manifest in various forms such as overbearing social customs and regressive socio-cultural practices that may adversely impact the BOP producers’ capacity to produce or reduce their access to the markets. The implications of our study for development organizations as well as for marketers include recognizing the importance of conducting market linkages programmes for BOP producers by efficient reduction of five market separations to accelerate market development at BOP, leading to developmental gains.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.004
Scholarly communication0.0030.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.028
GPT teacher head0.281
Teacher spread0.253 · 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 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

Citations22
Published2015
Admission routes1
Has abstractyes

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