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Record W2941111231 · doi:10.1145/3290605.3300586

Witchcraft and HCI

2019· article· en· W2941111231 on OpenAlexaff
Sharifa Sultana, Syed Ishtiaque Ahmed

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHappinessIdeologyPoliticsModernitySociologyEthnographyOccultMoralityPublic relationsEnvironmental ethicsAestheticsPsychologySocial psychologyPolitical scienceAnthropologyMedicineLaw

Abstract

fetched live from OpenAlex

While Human-Computer Interaction (HCI) research on health and well-being is increasingly becoming more aware and inclusive of its social and political dimensions, spiritual practices are still largely overlooked there. For a large number of people around the world, especially in the global south, witchcraft, sorcery, and other occult practices are the primary means of achieving health, wealth, satisfaction, and happiness. Building on an eight-month long ethnography in six villages in Jessore, Bangladesh, this paper explores the knowledge, materials, and politics involved in the local witchcraft practices there. By drawing from a rich body of anthropological work on witchcraft, this paper discusses how those findings contribute to the broader issues in HCI around morality, modernity, and postcolonial computing. This paper concludes by recommending ways for smooth integration of traditional occult practices with HCI through design and policy. We argue for occult practices as an under-appreciated site for HCI to learn how to combat ideological hegemony.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0060.056
Scholarly communication0.0220.011
Open science0.0010.009
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0170.002

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 head0.004
GPT teacher head0.210
Teacher spread0.206 · 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 designNot applicable
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

Citations91
Published2019
Admission routes1
Has abstractyes

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