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Record W2908338108 · doi:10.7202/1055449ar

Management of Knowledge Transfer for Capacity Building in Africa

2019· article· en· W2908338108 on OpenAlex
Emil Tchawe Hatcheu

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Comparative International Management · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican cultural and philosophical studies
Canadian institutionsnot available
Fundersnot available
KeywordsDiasporaEmigrationContext (archaeology)GlobalizationKnowledge transferPoliticsEconomic growthHuman capitalCapital (architecture)Development economicsBusinessPolitical scienceEconomicsMarket economyGeographyManagement

Abstract

fetched live from OpenAlex

Between sporadic remittances and training of a qualified manpower mastering new technologies, what does Africa expect from its diaspora to fill its development gap in the current context of globalization? When it comes to capital building, defined as the process or strategy to endow or increase the technical, managerial, or intellectual skills of an individual or a group, its know-how or knowledge, and financial capital or purchasing power, the World Bank and other development partners seem to grant priority to remittances. This paper strongly suggests that attention may be granted to the transfer of scientific knowledge between Africa and its diaspora, as many believe that progressing knowledge would help bring out a neglected source of wealth to fight the scourges responsible for political and economic backwardness in industrial countries. The development models based on the diaspora’s contribution in several countries and regions of the world, particularly in Asia, show the importance of knowledge transfer in capacity building. Similarly, Silicon Valley in California demonstrates the role of emigrants in the knowledge industry. As the brain drain is a normal phenomenon of globalization, emigration of African professionals is no more an obstacle to Africa’s development. Rather, the African diaspora constitutes a pool of human and investment capital that can strongly contribute to the continent’s development. From our point of view, the diaspora has an important role to play in capacity building, provided respective governments come up with sound policies to promote its participation. The diaspora’s participation in nation-building without physical relocation on the one hand, and the existence of the first generation of retired researchers and academics organized into civil society associations such as AED (Association for Education and Development) in Cameroon, on the other hand, constitute the pipeline of knowledge transmission. African partners and its diaspora can build a genuine partnership to create sustainable and competitive scientific institutions in Africa on this foundation. Improved governance, leadership, regulations, and immigration policy of sending and receiving countries are necessary for transnational scholarly/economic engagement.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.831
Threshold uncertainty score0.248

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 studies0.0000.000
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 head0.122
GPT teacher head0.368
Teacher spread0.246 · 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