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Record W2985378665 · doi:10.15700/saje.v39ns1a1797

Schooling experiences of children left behind in Zimbabwe by emigrating parents: Implications for inclusive education

2019· article· en· W2985378665 on OpenAlexaboutno aff
Mazvita Cecilia Tawodzera, Mahlapahlapana Themane

Bibliographic record

VenueSouth African Journal of Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationEmigrationEconomic growthDiasporaUnemploymentDocumentationPoliticsSociologyPolitical scienceQualitative researchGender studiesSocial scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Since the year 2000, a deepening political and economic crisis in Zimbabwe has forced parents to emigrate en masse to regional and international destinations such as South Africa, Botswana, Namibia, and the United Kingdom, the United States of America, Canada, Australia, and New Zealand respectively. Without guaranteed employment and with little knowledge of the education systems and the living conditions in the destination countries, most parents chose to initially emigrate on their own, settle down and later on send for their children. However, most of these children never joined their parents, owing to the various challenges that the majority of parents encountered in the diaspora: unemployment, lack of documentation, and poor living conditions. Against this background, this paper assesses experiences and challenges faced by the left-behind children (LBC) and explores these children’s perceptions of their interactions with teachers through inclusive education practices. A phenomenological research approach was adopted; in-depth interviews were used to collect data. The high schools were purposively sampled, one from a low-income area and the other from a high-income area in order to get a more pronounced picture of the experiences of LBC in the city. The results of the study indicate that LBC faced numerous challenges: excessive household chores, little help from guardians with homework, inadequate representation at school meetings, and non-payment of school expenses. Most children viewed their interaction with teachers as generally negative and reported that most of their needs were not met. The study recommends the crafting of inclusive education legislation for the country so that new vulnerabilities are holistically dealt with.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.008
GPT teacher head0.303
Teacher spread0.295 · 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

Citations11
Published2019
Admission routes1
Has abstractyes

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