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Record W4386137903 · doi:10.1007/s11125-023-09646-9

Teaching and teachers in the Sahel countries by 2030: The need to innovate in the face of adversity

2023· article· en· W4386137903 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProspects · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsUniversité du Québec à Montréal
FundersUniversité de Genève
KeywordsPaceFace (sociological concept)PrioritizationSet (abstract data type)Sustainable developmentPolitical scienceEducation for sustainable developmentSelection (genetic algorithm)Economic growthBusinessSociologyProcess managementComputer scienceGeographyEconomicsSocial science

Abstract

fetched live from OpenAlex

Abstract This article examines the educational and teacher-related policies in the Sahel region countries over the past decade and highlights main issues that hinder their ability to achieve the Sustainable Development Goals by 2030. The discrepancy between the current situation and the desired pace of change can be attributed to the lack of prioritization in educational and teaching policies. This article proposes an alternative approach, emphasizing the selection of a maximum of five objectives and providing the necessary means for their effective implementation. By adopting a focused approach, the Sahel region can make strides in overcoming educational challenges and aligning with the goals set for 2030.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.315
Teacher spread0.301 · 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