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Record W1968910552 · doi:10.1108/edi-07-2013-0055

Relative deprivation, self-interest and social justice: why I do research on in-equality

2014· article· en· W1968910552 on OpenAlexaffabout
Eddy S. Ng

Bibliographic record

VenueEquality Diversity and Inclusion An International Journal · 2014
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAutoethnographyOriginalityNarrativeFeelingValue (mathematics)ReflexivityInterpretation (philosophy)SociologySubjectivityRelative deprivationSelfEconomic JusticeSocial psychologyNarrative inquiryIdentity (music)PsychologyEpistemologyGender studiesQualitative researchAestheticsSocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to offer an insight into why men do research on in-equality. Design/methodology/approach – The author utilizes autoethnography, as a form of self-reflection, to help make sense of the own experiences and to connect it with the broader world. It is a narrative based on personal experiences which connects the author's biography with his research endeavours. It also enables to engage in self-analysis and self-awareness of the motives for conducting research on in-equality. Findings – In this narrative, the author shares his journey as an equality scholar, and how his multiple identities as a visible minority, an immigrant to Canada, and a gay person shapes my worldview, attitudes, and beliefs, which in turn influences his own work on equality and diversity. The narrative is based on the intersection of multiple identities, and not just solely based on the author's gender. The attribute feeling deprived on behalf of others, rational self-interest, and social justice as the chief reasons for engaging in in-equality research. Research limitations/implications – Autoethnography is inherently subjective, based upon the author's own biases and interpretation of events, but the subjectivity can also be an opportunity for intentional self-awareness and reflexivity. Given the multiple identities that the author holds, some of the experiences recounted here may be unique to the author, and some may be shared with others. Thus, it is not the author's intention to represent, in general, why men do in-equality research. Originality/value – This autoethnography has allowed the author the opportunity to be self-aware of the complexity of the multiple identities. This self-awareness also allows the author to be more respectful, authentic, and inclusive of others. The author hopes that these reflections will resonate with some of you, and perhaps inspire one to engage in similar work, for reasons that are unique to one and all.

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)0.074
metaresearch head score (Gemma)0.108
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: none
Teacher disagreement score0.074
Threshold uncertainty score0.389

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.108
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.061
Scholarly communication0.0140.017
Open science0.0020.010
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0020.001

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 head0.214
GPT teacher head0.488
Teacher spread0.274 · 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

Citations12
Published2014
Admission routes2
Has abstractyes

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