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Record W2527797512

Teachers' cultural values and accountability in Nigeria

2016· dissertation· en· W2527797512 on OpenAlexaff
Olufunmilayo Familusi

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicAfrican Education and Politics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAccountabilityBureaucracyDescriptive statisticsVariance (accounting)Significant differencePsychologyPolitical scienceStatisticsAccountingBusinessMathematics
DOInot available

Abstract

fetched live from OpenAlex

This study investigates teacher‟s cultural values and accountability in Nigeria. A questionnaire developed by Professor Rosenblatt (University of Haifa, Israel) was used to gather quantitative data from 483 secondary teachers across Oyo, Osun, Ogun, and Lagos States in Southwest Nigeria. Data collected were analyzed using percentages, descriptive statistics, and analysis of variance (ANOVA). The findings show that Nigerian teachers have high dispositions towards both bureaucratic (external) and internal (professional) accountability and their scores for internal accountability (M= 4.4286; SD= 0.5726) were higher than their scores for external accountability (M= 3.9759; SD = 0.5575). Geographical locations made a significant difference in the scores. Teachers from urban and suburban areas demonstrate higher scores than teachers from the rural in both bureaucratic (external) and internal (professional) accountability

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.344
Teacher spread0.308 · 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 designQualitative
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

Citations1
Published2016
Admission routes1
Has abstractyes

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