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Record W4283802292 · doi:10.23962/ajic.i29.14245

Value Creation and Socioeconomic Inclusion in South African Maker Communities

2022· article· en· W4283802292 on OpenAlexfundno aff
Chris Armstrong, Erika Kraemer‐Mbula

Bibliographic record

VenueThe African Journal of Information and Communication (AJIC) · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsnot available
FundersAmerican University in CairoSocial Sciences and Humanities Research Council of CanadaNational Research FoundationUniversity of Cape TownInternational Development Research CentreUniversity of JohannesburgUniversity of Ottawa
KeywordsCognitive reframingValue (mathematics)Socioeconomic statusInclusion (mineral)SociologyPsychologySocial psychologySocial scienceDemographyMathematicsStatisticsPopulation

Abstract

fetched live from OpenAlex

In socioeconomic environments affected by high and persistent income inequalities and unemployment, there is a need for participative approaches to innovation in support of socioeconomic inclusion. This article explores the features of collective action, in support of socioeconomic inclusion, identified in South African maker communities. Drawing on data from interviews with participants in seven maker communities, the study explores the kinds of value that participants experience through being part of these communities. Value creation is assessed in terms of the five overlapping cycles of value that Wenger et al. (2011) propose are present in successful communities and networks: immediate value, potential value, applied value, realised value, and reframing value. The study finds that all five value cycles are present in the experiences expressed by the South African maker community participants. The value is found to be particularly pronounced in the immediate value and applied value cycles. In respect of socioeconomic inclusion, the findings point to strong currents of social inclusion in the immediate value cycle, and strong elements of both social and economic inclusion in the applied value, realised value, and reframing value cycles.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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 designQualitative
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

Citations0
Published2022
Admission routes1
Has abstractyes

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