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Record W3041006327 · doi:10.5430/ijfr.v11n4p289

The Effect of the Relationship Between Cash Flows From Operating Activities and Earnings per Share in Jordan

2020· article· en· W3041006327 on OpenAlexvenueno aff
Yaser Mohd Hamshari

Bibliographic record

VenueInternational Journal of Financial Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessEarningsCash flowStock exchangeEarnings per shareCashOperating cash flowFinanceLegislationExploitService (business)AccountingMarketing

Abstract

fetched live from OpenAlex

The study assumes that there is a relationship between the cash flows from the operational activity and the earnings per share. The companies listed on the Amman Stock Exchange have been studied, including the banking sector, the insurance companies sector, and the service sector (education sector). One of the objectives of the study was to know that the administration exploits all available capabilities and achieve quality in profits through activities, operating, financing and investment in a way that achieves a sense of security for the investor and who is waiting for the reward that he invested his money in order to obtain a return that meets what is expected. Therefore, it was necessary to educate users of the data of the importance of understanding and studying the list of cash flows as an analytical tool.It is assumed that the conclusion of this study is that there is a strong relationship between cash flows from operating activity and earnings per share (earnings per share) with a need to pay attention to operational activity and provide and create economic conditions and laws and legislation that help to strengthen and achieve voluntary power because it reflects the continuity of facilities and companies.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.052
GPT teacher head0.331
Teacher spread0.278 · 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 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

Citations6
Published2020
Admission routes1
Has abstractyes

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