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Record W4317648125 · doi:10.51976/ijari.221436

An Inductive Analysis of Relation Maintenance Strategies with Employees (An Analysis of Public Sector in India)

2014· article· en· W4317648125 on OpenAlexaboutno aff
Sneha Sneha

Bibliographic record

VenueInternational Journal of Advance Research and Innovation · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Business Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTransparency (behavior)PillarQuarter (Canadian coin)WorkforcePublic relationsBusinessInformation and Communications TechnologyMarketingRelation (database)EngineeringEconomicsEconomic growthPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The slowdown in the economy has put a great deal of pressure on different corporate to cut down on the vicarious expenditures that they have been doing on the name of maintain relationship with their internal customers i.e. employees. Communication channels form the lifeblood of the organization. Organization today are searching out ways to bring transparency in their system by opening up of communication channels for their employees. The paper would primarily focus on different strategies being adopted by inclusive to foster participation from different quarter of their workforce. The central pillar of the paper would revolve around advent of suggestion schemes and open door policy being put in to practice in Indian firms. Paper would also throw a brief light on Satyam’s and Infosys way of providing open communication platform to their employees.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.094
GPT teacher head0.352
Teacher spread0.258 · 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
Published2014
Admission routes1
Has abstractyes

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