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Record W6969404134 · doi:10.5281/zenodo.8256489

The Nigeria We Want - NYFF

2023· report· en· W6969404134 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typereport
Languageen
Field
Topic
Canadian institutionsMastercard Foundation
Fundersnot available
KeywordsNational developmentCitizen journalismParticipatory planningFoundation (evidence)Strategic planningProcess (computing)

Abstract

fetched live from OpenAlex

The Nigeria We Want is a report by Nigerian youths on the future. It is a critical review of the past, present and the future by the youths to present alternative scenarios of the future, a shared vision and a strategic agenda for national transformation. The exercise adopted a participatory process and included youth delegates from across the nation who participated in regional retreats across the six geo-political zones in Nigeria and two national retreats in Abuja. The process also included review workshops with a sub-committee of the national delegates in-between the two national retreats. These provided the opportunity for an in-depth review of the draft report. The exercise was led by the LEAP Africa Team with support from the NYFF Advisory Board. A team of faculty led the design and facilitation of the exercise and preparation of the report. The NYFF is funded by Ford Foundation and MacArthur Foundation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0230.005

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 head0.132
GPT teacher head0.322
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2023
Admission routes1
Has abstractyes

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