MétaCan
Menu
Back to cohort
Record W2159839846 · doi:10.5539/jsd.v6n11p98

The Traditional Pottery and Social Engineering: Beyond the Apprenticeship Façade

2013· article· en· W2159839846 on OpenAlexvenueno aff
Chris Echeta

Bibliographic record

VenueJournal of Sustainable Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education and Engineering Focus
Canadian institutionsnot available
Fundersnot available
KeywordsApprenticeshipPotteryExcellenceSustainabilityProduct (mathematics)BusinessMarketingSociologyManagementPublic relationsEconomicsHistoryArchaeologyPolitical scienceLawMathematics

Abstract

fetched live from OpenAlex

The sustainability lifeline of traditional pottery in Nigeria is hooked to apprenticeship programmes. Not only does it ensure a turn-over of job openings for the teeming jobless populace, it engages the idle mind meaningfully by distracting it from succumbing to anti-social lifestyle. Apprenticeship, in the course of time, matures into mastery of raw material behaviour and the techniques of production. This dovetails into social re-moulding and this re-engineers the benefitting environment for the overall good. The mention of traditional pottery to the uninformed creates the impression of vessels of crudity and the absence of technical excellence. Contrary to that, it is a tradition of incredible product finesse and complicated technical processes, some of which are still being researched into today. The area has matured into a wholesome body of knowledge routinely handed over, through the apprenticeship system, from one generation to the next without the loss of the tiniest fragment of relevant information. This paper peers into the apprenticeship arena and tries to locate other social benefits which lie side by side with pottery skill acquisition. These benefits tend to re-engineer the societal structure and their effects continue to socially multiply beyond the apprenticeship façade.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.017
GPT teacher head0.220
Teacher spread0.203 · 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 designNot applicable
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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sustainable DevelopmentSame topicDiverse Education and Engineering FocusFrench-language works237,207