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Record W4409605166 · doi:10.61091/jcmcc127b-274

Evaluation model of auxiliary employability of special population based on AHP-FUZZY algorithm

2025· article· en· W4409605166 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
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

VenueJournal of Combinatorial Mathematics and Combinatorial Computing · 2025
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Technologies in Various Fields
Canadian institutionsnot available
Fundersnot available
KeywordsEmployabilityFuzzy logicAnalytic hierarchy processComputer sciencePopulationAlgorithmArtificial intelligenceMathematicsOperations researchPsychologySociologyDemography

Abstract

fetched live from OpenAlex

In order to realize the quantitative management of the quality of higher education, this paper puts forward an evaluation model of auxiliary employability of special people under the concept of public employment service based on AHP-FUZZY algorithm.The phase space distribution structure model of special people's auxiliary employability under the concept of public employment service is constructed, the index parameter set of special people's auxiliary employability under the concept of public employment service is established, the fuzzy association rule distribution set is constructed by principal component analysis and fuzzy parameter estimation, and the association rule characteristic quantity of special people's auxiliary employability under the concept of public employment service is extracted.Advanced statistical analysis methods, such as principal component analysis, big data fusion analysis and fuzzy detection model, are adopted to classify the multi-dimensional attribute features of special people's auxiliary employability under the concept of public employment service, and the data is partitioned and scheduled in the fuzzy clustering center according to the differences of statistical feature parameters of employability analysis reports, and the feature decomposition model of special people's auxiliary employability under the concept of public employment service is constructed.The auxiliary employability of special people under the concept of public employment service is fused by blocks and the regional structural parameters are reorganized.The binary structural characteristics of auxiliary employability analysis of special people under the concept of public employment service are reconstructed in the subspace fusion database.According to the reconstruction results, fuzzy clustering is carried out under principal component analysis and fuzzy parameter estimation, and the optimal evaluation of auxiliary employability of special people under the concept of public employment service is realized.Based on SPSS statistical analysis software and Matlab simulation tool, the empirical simulation analysis of the evaluation shows that the characteristic clustering of the evaluation of the auxiliary employability of special population under the concept of public employment service is good, the reliability of the

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.639
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.292
Teacher spread0.272 · 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