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Record W2966166573

A study on welfare policies of Amara Raja Power System Limited: A case study in Tirupati

2019· article· en· W2966166573 on OpenAlexaboutno aff
B. Ramachnadra Reddy, Duggani Yuvaraju

Bibliographic record

VenueInternational journal of advance research, ideas and innovations in technology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessBachelorQuarter (Canadian coin)RecreationSWOT analysisData collectionWelfareQuality (philosophy)RajaMarketingOperations managementEngineeringEconomicsStatisticsMathematicsGeography
DOInot available

Abstract

fetched live from OpenAlex

I conducted a Survey Method through Structured Questionnaires in the Employees of ARPSL Tirupati. The convenience sampling procedure is used for the data collection, sampling size is116 through Personal Interview and Percentage analysis and Chi-square tests are used. Finally, in this paper, I found the result that the Majority of the respondents said that Medical and First aid facilities provided by the Company are Excellent. Canteen facilities are good because the cleanliness maintained, proper storage of raw materials, food served is nutritious quality and quantity of food served is good. Working conditions of the company in respect to Ventilation, Lighting, Temperature, Seating arrangements, cleanliness inside working premises are very good. Employee satisfaction levels on Social security benefits like PF, ESI, Gratuity, SAS and Benevolent Fund schemes provided by the company is good. Transport facilities, Bachelor Hostel facilities, Family quarter’s facilities, Recreation facilities provided by the company are good.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.367
Teacher spread0.341 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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