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Record W3215353726 · doi:10.23977/aetp.2021.59018

The Construction of the Back-feeding Mechanism of the Alumni Association of Local Colleges and Universities

2021· article· en· W3215353726 on OpenAlexvenueno aff
Dan Yao

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIdeological and Political Education
Canadian institutionsnot available
Fundersnot available
KeywordsMechanism (biology)Order (exchange)Higher educationAssociation (psychology)Public relationsPolitical scienceSociologyPedagogyBusinessPsychologyLaw

Abstract

fetched live from OpenAlex

The development of higher education and the extensive development of foreign exchanges have increasingly revealed the important role of alumni resources in the development of colleges and universities, and the establishment of alumni associations has received more and more attention from colleges and alumni associations. This article focuses on the research on the back-feeding mechanism of the local college alumni associations. Based on the literature, it has a general understanding of the relevant theories of the local college alumni associations. Then, in order to further understand the current situation of the back-feeding Methods Investigate it. The results of the investigation show that in the current stage of the problems in the back-feeding mechanism of college alumni associations, the lack of alumni contact accounts for about 46%, followed by the insufficient development of alumni resources.

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.003
Science and technology studies0.0060.010
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.009
GPT teacher head0.326
Teacher spread0.317 · 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 designNot applicable
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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