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Record W4287186149 · doi:10.5281/zenodo.4735685

Meritocracy in the Educational System

2021· article· en· W4287186149 on OpenAlex
Aroesiri Erivwo, Elizabeth Varghese, Anthony Mathai, Tasmia Afrin

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCentral Asia Education and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsMeritocracySociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

A meritocratic education system, by nature, is one where students are enabled to accomplish achievements, and receive corresponding rewards, regardless of outside factors. The common norm in schools is that achievement based on merit explains school success, and that merit is the only means of the upward mobility of all students in regards to societal status, regardless of age, gender, ethnicity, current social status, etc. The primary motive of this study was to determine whether education reflected this meritocratic nature and if education is merely a scale of academic achievement by examining trends within students. The materials we used to justify our results were demographic trends, school performance (self-assessment scale), and family background. Data was collected through surveys distributed to students (n = 351) with a mean age of 16.2. Our study was run within three main regions: United States, Canada, and Nigeria, and the results indicated that even though there is evidence of a correlation of a meritocratic nature in the education system (from the contingency tables), it fails to take into account socioeconomic factors, with other external factors affecting student achievement such as the generational cycle. Factors of constraint that are evident in our study include an uneven bell curve based on the categories of students surveyed, inequitable (biased) self-assessment responses, and achievement gaps in the education system.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.003

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 head0.035
GPT teacher head0.294
Teacher spread0.259 · 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