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Record W3176737119 · doi:10.23977/aetp.2021.53007

Study on the Employment Concept of College Students in the Post-Epidemic Era--The reflection on the course “College Students Career Planning” of Tibet University

2021· article· en· W3176737119 on OpenAlexvenueno aff
Mengjia Zhang, Haoran Gong

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentCareer planningContradictionChinaPerspective (graphical)CognitionScale (ratio)PsychologySociologyPolitical scienceMedical educationPublic relationsEconomic growthPedagogyEconomicsMedicineGeographyLaw

Abstract

fetched live from OpenAlex

The new crown epidemic that has swept the world has had a huge impact on the international and domestic economies. China's job market has also been greatly affected. The overall employment situation is severe and the risk of large-scale unemployment is prominent. Due to the weak awareness of college students' career planning, they lack scientific and reasonable career planning. Therefore, the contradiction between the higher employment expectations of college students and the severe employment reality in the post-epidemic era appears to be very prominent. With the continuous increase in the number of college graduates in Tibet, Tibet University has taken the course “Career Planning for College Students” as an important carrier to guide students to establish a correct outlook on career choice and employment. From the perspective of students, it explores the employment concept of college students in the post-epidemic era from three aspects: basic information, self-cognition, and employment cognition.

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)0.002
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.402
Teacher spread0.333 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueAdvances in Educational Technology and PsychologySame topicCOVID-19 Pandemic ImpactsFrench-language works237,207