MétaCan
Menu
Back to cohort
Record W3110973327 · doi:10.17762/de.vi.970

Research on Sense of Fulfillment, Happiness and Security of Talents in New Era

2020· article· en· W3110973327 on OpenAlexvenueno aff
Hao Wang Yunna Liu

Bibliographic record

VenueDesign Engineering · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsHappinessResearch ObjectPsychologyQuality (philosophy)Object (grammar)Social psychologyPublic relationsBusinessPolitical scienceComputer scienceEpistemologyBusiness administrationArtificial intelligence

Abstract

fetched live from OpenAlex

This research chooses the talents of the new era as the research object and the sense of fulfillment, happiness and security as the foothold. Through the research on the sense of fulfillment, happiness and security of the talents in the new era, the paper demonstrates talents how to make a good career planning and development, so as to improve the quantity and quality of employment. After consideration of the relationship between the sense of fulfillment, happiness, and security of talents, the paper illustrates talents should cognize the overall status of career development, increase self-awareness of values, interest and skills, know the occupation choices and understand the industry in New Era.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.081
GPT teacher head0.266
Teacher spread0.185 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueDesign EngineeringSame topicHuman Resource and Talent ManagementFrench-language works237,207