MétaCan
Menu
Back to cohort
Record W1971374712 · doi:10.5539/ibr.v3n2p24

Mars, Venus and Gray: Gender Communication

2010· article· en· W1971374712 on OpenAlexvenueno aff
Kamarul Zaman Ahmad, Kalaiselvee Rethinam

Bibliographic record

VenueInternational Business Research · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
Fundersnot available
KeywordsGray (unit)VenusMars Exploration ProgramPsychologyTest (biology)Social psychologyAstrobiologyGeologyMedicine

Abstract

fetched live from OpenAlex

This research tests the propositions relating to gender communication by Gray (1992) in his book titled “Men are from Mars, Women are from Venus” This book has been the source of gender-related controversy since its publication. The sample consisted of 182 executives and non-executives (73 males and 109 females). T-test results show that out of 23 statements made by Gray (1992), only 8 were supported, 10 were not supported and 5 were actually true for the opposite gender. This research is indeed timely in that it addresses the long disservice to women. So the way forward into the future would be to train people on how to communicate better by making them aware that different people have different preferences and styles of communication, rather than essentializing and gender-stereotyping.

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)0.003
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0030.005
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.142
GPT teacher head0.458
Teacher spread0.316 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueInternational Business ResearchSame topicMedia, Gender, and AdvertisingFrench-language works237,207