MétaCan
Menu
Back to cohort
Record W2738785079 · doi:10.1596/28053

Higher Education Governance in Guinea

2015· book· en· W2738785079 on OpenAlexfundno aff

Bibliographic record

VenueWorld Bank, Washington, DC eBooks · 2015
Typebook
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsnot available
FundersSoutheastern Ontario Academic Medical OrganizationBoston CollegePohang University of Science and TechnologyWorld Bank Group
KeywordsNew guineaCorporate governancePolitical scienceBusinessSociologyEthnologyFinance

Abstract

fetched live from OpenAlex

The World Bank’s Country Partnership
\n Strategy (CPS) for Guinea in FY 2014–171 confirmed the
\n Government’s priority to build 21st century skills for
\n improved employability and to implement systemic reforms.
\n Guinea is emerging from years of political and economic
\n isolation and instability. The democratic election of
\n President Alpha Condé has opened the door for the
\n international donor community, including the World Bank, to
\n come forward and support the new government. The World Bank
\n will partner with the Government of Guinea to develop
\n systems that will ‘improve lagging human development
\n indicators for absolute poverty reduction, through more
\n efficient and transparent allocation of resources, and to
\n build shared prosperity by aligning the business environment
\n and education system with Guinea’s economy’ (World Bank,
\n 2013, pp. 1). This is in line with the government’s
\n priorities, as per the Third National Poverty Reduction
\n Strategy Paper (PRSP3) approved in 2013. The PRSP3 aims to
\n reduce poverty and to create and sustain a vibrant private
\n economy by maximizing rents from Guinea’ssubstantial mining
\n sector. The Bank supports the Government’s agenda on
\n improving human capital by: (a) promoting both the quantity
\n and quality of education, and (b) upgrading skills for the
\n needs of emerging and export-oriented sectors such as
\n agriculture, tourism, mining, and telecommunications and
\n Information and Communications Technology (ICT). In 2012,
\n the Government requested special support from the Bank in
\n the form of technical assistance to conduct an analysis of
\n the higher education system. This analysis will be used to
\n prepare a comprehensive higher education strategy to meet
\n the needs of both the economy and the labor market. Since
\n the early 2000s, the Bank had limited involvement in this
\n critical sub-sector. Per the Government’s request, the Bank
\n mobilized resources to engage in policy and analytical work
\n in the areas of governance, financing, and diagnostic of
\n skills demand and supply from a new employer survey prepared
\n specifically under this technical assistance project.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.379
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueWorld Bank, Washington, DC eBooksSame topicEconomic Growth and DevelopmentFrench-language works237,207