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Record W6990019610

A CONTENT ANALYSIS OF THE MISSION STATEMENTS OF IRAN, TURKEY, INDIA AND UNITED STATES PHARMACEUTICAL COMPANIES

2014· article· en· W6990019610 on OpenAlexaboutno aff

Bibliographic record

VenueRePEc: Research Papers in Economics · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Strategy and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)TurkishContent analysisPharmaceutical industryMission statementFocus (optics)
DOInot available

Abstract

fetched live from OpenAlex

Pharmaceutical companies play a critical role in healthcare economy. Articulating mission statement of a Pharmaceutical company results in guiding strategies and activities of the firm. In this survey, mission statements of Iranian, Turkish, Indian and American pharmaceutical companies are analyzed. By using content analysis, frequencies of nine elements of the mission statement according to Fred R. David including: customers, product/service, market, technology, survival/growth/profitability, philosophy, self-perception, public image and employee were investigated. 98 mission statements of pharmaceutical companies (32 iranain companies, 16 Turkish companies, 30 Indian companies, and 20 American companies) were analyzed. Simple correspondence analysis was used to extract the perceptual map. Results indicate that two dimensions of perceptual map include: focus of mission (throughput or input/output), and focus of mission elements (market or support). Iranian companies placed on the quarter of throughput /support, American and Turkish companies placed on the quarter of throughput/market. Indian companies placed on the quarter of input and output/market.

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 score0.103
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.066
GPT teacher head0.333
Teacher spread0.267 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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