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Record W7133234165 · doi:10.53724/inspiration/v10n2.05

Section 69 of BNS 2023: Balancing Justice and Safeguards Against False Allegations in Cases of Sexual Intercourse by Deception

2025· article· W7133234165 on OpenAlexaboutno aff
Dr. Jai Prakash Kushwah, Suraj Pratap Singh Kushwah

Bibliographic record

VenueResearch Inspiration · 2025
Typearticle
Language
FieldSocial Sciences
TopicJury Decision Making Processes
Canadian institutionsnot available
Fundersnot available
KeywordsDeceptionMisrepresentationSafeguardingSection (typography)Coercion (linguistics)Economic JusticeCriminal justiceAllegation

Abstract

fetched live from OpenAlex

The enactment of Section 69 of the Bharatiya Nyaya Sanhita (BNS), 2023, marks a significant shift in Indian criminal law by criminalizing sexual intercourse obtained through deceitful means. While the provision aims to protect individuals from fraudulent consent violations, it also raises concerns regarding the potential for misuse and false allegations. This research critically examines the scope, interpretation, and judicial challenges associated with Section 69, focusing on the delicate balance between safeguarding victims' rights and preventing wrongful prosecution.One of the primary concerns is the subjective nature of deception, particularly in cases involving false promises of marriage, misrepresentation of identity, or coercion through fraudulent means. Judicial precedents under Section 375 of the IPC (now replaced) have already seen debates over distinguishing genuine breaches of trust from criminal offenses. This study evaluates how Section 69 differs from previous laws, how courts might interpret deceit in sexual relationships, and what safeguards exist to prevent frivolous complaints.A comparative analysis with global legal frameworks, including laws from the United States, the United Kingdom, and Canada, provides insight into how other jurisdictions handle similar cases and whether India's legal system needs additional safeguards. Furthermore, the paper explores potential evidentiary challenges, the burden of proof, and the risk of reputational damage caused by false accusations.To ensure judicial fairness, this research suggests policy recommendations, including stricter evidentiary requirements, preliminary screening mechanisms, and clearer judicial guidelines for handling cases under Section 69. Ultimately, this paper aims to contribute to the ongoing legal discourse by advocating for a balanced approach one that upholds victim protection while preventing the weaponization of the law for malicious intent.

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)0.010
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.009
Scholarly communication0.0050.002
Open science0.0020.003
Research integrity0.0060.005
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 head0.093
GPT teacher head0.463
Teacher spread0.369 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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