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Record W2610169815 · doi:10.19044/esj.2017.v13n10p307

Essaie de Description du Système Foncier Congolais d’avant Le Contact Formel Avec La Civilisation Occidentale

2017· article· en· W2610169815 on OpenAlexaff
Marie-Bernard Dhedya Lonu, Markus Gehrin, Marie-Claire Cordonier, Michel Ilume Moke, Salomon Mampeta Wabassa

Bibliographic record

VenueEuropean Scientific Journal ESJ · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPossession (linguistics)CivilizationProperty (philosophy)DivinityEthnologyCONQUESTCommunity propertyHistoryGeographySociologyHumanitiesPhilosophyTheologyArchaeologyAncient historyEpistemology

Abstract

fetched live from OpenAlex

The present study focuses on the description of the Congolese land system prior to formal contact with Western civilization. Contrary to what has been imagined, the natives of Congo have understood the notion behind landed property. This property is rather peculiar in that it does not fulfill all the criteria imposed by modern law. A few elements have enabled us to describe it. The notion of landed property has been made known to the natives. This property is established at the moment the pacific takes possession of it or by conquest of the soil. It is essentially influenced by the beliefs that characterize traditional Africa. However, the beliefs in the existence and interaction of the world of the dead with that of the living, and the beliefs in the divinity of the soil, makes it possible to specially guide the perception of landed property. Moreover, the community character directs land ownership towards collective ownership rather than individual ownership.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0030.001
Open science0.0010.000
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 head0.021
GPT teacher head0.210
Teacher spread0.190 · 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 designObservational
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

Citations0
Published2017
Admission routes1
Has abstractyes

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