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Record W2913129655 · doi:10.6000/1929-7092.2019.08.16

Privatization Process and Talent Management in Angola

2019· article· en· W2913129655 on OpenAlexvenueno aff
Renato Lopes Da Costa, Marta Correia Sampaio, Isabel Miguel

Bibliographic record

VenueJournal of Reviews on Global Economics · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)Talent managementBusinessProcess managementComputer scienceMarketing

Abstract

fetched live from OpenAlex

The problem of the privatization process began in the 1940s, even though it only really began to gain a prominent place in the entrepreneurial path, about 50 years later. The processes of privatization of the world economies, which led to the triggering of a set of cooperative strategies based on the State-owned enterprises privatization, and, of course, all these events, had repercussions also in Angola. Based on an investigation of a pragmatic or inductive nature, based on a non-probabilistic sample, due to the lack of studies and information about the phenomenon of Angola’s privatization during the period from colonial independence to the present. This article aims to develop this subject by presenting, on the one hand, a set of causes that were the basis of the failure in the privatization processes taken place in Angola between 1989 and 2005 and which degenerated into the collapse of its corporate network. And, on the other hand, it presents an idea of the possible impact that these privatization processes failures had, and still have, on Talent Management by Angolan organizations. It also presents a set of suggestions which could be considered in future privatization processes that may occur by building a more consistent business structure in economic and business terms.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.473

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 communication0.0000.001
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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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 designNot applicable
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

Citations1
Published2019
Admission routes1
Has abstractyes

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