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Record W2482920529 · doi:10.1177/194277861400700108

The World is Bumpy: Power, Uneven Development and the Impact of New ICTS on South African Manufacturing

2014· article· en· W2482920529 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHuman Geography · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsTrinity College
Fundersnot available
KeywordsICTSCompetition (biology)Information and Communications TechnologyEmerging technologiesPower (physics)InequalityBusinessEconomic geographyEconomic growthEconomicsPolitical science

Abstract

fetched live from OpenAlex

Numerous academics and policy makers now assert Sub-Saharan Africa's (SSA) marginalization in the global economy is being reversed by an information technology revolution. However, while many claims are made for new ICTs - and mobile phones in particular - very little research has been done on the precise ways in which firms use these technologies and their developmental impacts. Drawing on over fifty firm-level interviews, this paper examines evidence of the uses and impacts of new ICTs in the wood products industry in Durban, South Africa and its surrounding region. In contrast to assumptions in much of the literature, it finds that rather than primarily being used to connect to global markets, they are most commonly used as technologies of local labour control and inter-firm competition. Consequently the use of these technologies may deepen existing inequalities and uneven development, and in some instances disinformationalisation, rather than reduce or overcome them.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.014
GPT teacher head0.230
Teacher spread0.216 · 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