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Indigenous Peoples in Africa

2017· reference-entry· en· W2776938205 on OpenAlexaff
Renée Sylvain

Bibliographic record

VenueOxford Research Encyclopedia of African History · 2017
Typereference-entry
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsIndigenousSolidarityHuman rightsPolitical scienceState (computer science)RedressIndigenous rightsScholarshipGender studiesSociologyLawPolitics

Abstract

fetched live from OpenAlex

Abstract Moringe ole Parkipuny addressed the United Nations Working Group on Indigenous Populations (UNWGIP) in 1989 and, for the first time, opened up discussion of the idea that certain groups of hunter-gathers and pastoralists in Africa merited the status of indigenous peoples. Local activists and international organizations took up the cause in the following decades. Several international conferences resulted in new forms of activism, the reformulation of local identities, and a growing body of scholarship addressing African indigeneity. As NGOs built solidarity among relatively scattered groups of pastoralists and hunter-gatherers, often skeptical state governments initially resisted what they saw as demands for recognition of status and claims to “special rights.” Disagreements between state interests and newly organized indigenous groups were expressed at the United Nations during the process of adopting the Declaration on the Rights of Indigenous Peoples (UNDRIP); but as the idea of indigeneity evolved through such discussions, African governments gradually came on board. International activism and work done by the African Commission on Human and Peoples’ Rights play significant roles in convincing African states to accept the concept of “indigenous peoples.” The issue of developing a definition of “indigenous peoples” appropriate for Africa remains unsettled and continues to present challenges. Mobilization among marginalized groups on the African continent itself, however, has presented NGOs, activists, states, and courts with the opportunity, through well-publicized struggles and several landmark legal cases, to refine the category to better fit with African contexts.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.092
GPT teacher head0.345
Teacher spread0.253 · 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
Published2017
Admission routes1
Has abstractyes

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