Update README.md

# ⚠️ Content Warning: High-Risk Mental Health Triggers
**This dataset contains text related to suicidality, self-harm, and acute psychological distress.** It is intended solely for the purpose of training safety models and researching crisis intervention. Reader discretion is advised.

## Dataset Description

**HiddenSignals-v1** is a specialized corpus designed to address the "Clinical Gap" in current AI safety models. While standard datasets focus on explicit clinical terminology (e.g., *"I want to commit suicide"*), this dataset aggregates **implicit, slang-based, and evasive distress signals** (e.g., *"I'm checking out,"* *"sewerslide,"* *"buying a ticket to Switzerland"*).

The data is collected via **MindBridge**, an anonymous peer-support platform, and annotated by a team of clinical psychology researchers using the **Columbia-Suicide Severity Rating Scale (C-SSRS)**.

* **Curated by:** MindBridge Research Lab
* **Funded by:** [Proposed] OpenAI AI Mental Health Research Grant
* **Language:** English (Internet Vernacular / Gen-Z Slang focus)
* **License:** CC-BY-NC-SA 4.0 (Non-Commercial, Research Use Only)

### Research Goal
To enable Large Language Models (LLMs) to detect "False Negatives" in crisis scenarios—identifying users who are at risk but are using algorithmic evasion techniques or sub-cultural slang to mask their intent.


## Dataset Structure

### Data Instances
A typical data point consists of an anonymized chat segment, the specific slang term identified, and a verified clinical risk label.

```json
{
"id": "mb_7a8b9c_2025",
"text": "honestly i think i'm just gonna minecraft myself tonight, i'm so cooked.",
"context_tag": "gaming_metaphor",
"detected_slang": ["minecraft myself", "cooked"],
"standard_model_prediction": "neutral",
"clinical_risk_label": 4,
"risk_description": "Active Ideation with Method (c-ssrs-4)"
}
```

### Data Fields
* `id`: Unique hash for the segment (k-anonymity enforced).
* `text`: The raw text segment (PII stripped).
* `context_tag`: The linguistic category (e.g., `gaming_metaphor`, `TikTok_slang`, `algorithmic_evasion`).
* `standard_model_prediction`: The baseline output from GPT-4o-mini (used to highlight the gap).
* `clinical_risk_label`: Integer (0-5) based on the C-SSRS scale.
* **0:** No Risk / Venting
* **1:** Wish to be Dead
* **2:** Non-Specific Active Ideation
* **3:** Active Ideation with Method (Implicit)
* **4:** Active Ideation with Method (Explicit)
* **5:** Active Ideation with Plan & Intent (Imminent)


## Dataset Creation

### Curation Rationale
Standard safety filters often over-censor vague sadness while missing high-risk slang. This dataset is curated specifically to capture the "Long Tail" of distress language that commercial models miss.

### Source Data
* **Platform:** MindBridge Web App (Peer-to-Peer Chat).
* **Collection Process:** Users opt-in to the "Research Contribution" mode. Conversations are filtered for high-sentiment velocity using **MentalBERT**. Segments containing potential slang are flagged for human review.

### Annotation Process
All data is annotated by a two-person team:
1. **Primary Annotator:** Graduate Clinical Psychology Researcher (St. Petersburg State University).
2. **Validator:** Lead Investigator (Clinical Psychology Candidate).
* *Inter-Rater Reliability:* Disagreements are resolved via a third-party consensus review.


## Ethics & Safety

### PII & Anonymity
We utilize a strict **K-Anonymity** pipeline.
1. **Pre-Processing:** All text is run through a Named Entity Recognition (NER) scrubber to redact names, locations, phone numbers, and emails.
2. **Unlinking:** Chat logs are stripped of IP addresses and user IDs before entering the dataset.

### Usage Restrictions
* **Permitted Use:** Academic research, AI safety alignment, training crisis detection classifiers.
* **Prohibited Use:** Generating toxic content, training "uncensored" models to mock mental health, or commercial insurance risk profiling.

### "Red Switch" Protocol
During data collection, if a user exhibits "Imminent Risk" (Level 5), the data collection is immediately suspended, and the user is routed to emergency services via the MindBridge Safety Protocol. This data is **excluded** from the public dataset to protect the privacy of acute crisis events.


## Citation

If you use this dataset, please cite the following:

```bibtex
@dataset {mindbridge_hiddensignals_2025,
author = {MindBridge Research Lab},
title = {HiddenSignals-v1: A Dataset of Implicit Suicidal Ideation},
year = {2025},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/mindbridge/hiddensignals}
}
```

README.md

@@ -1,3 +1,16 @@
----
-license: odbl
----
+---
+license: cc-by-sa-4.0
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- mental-health
+- psychology
+- safety-alignment
+- crisis-detection
+- suicide-prevention
+pretty_name: 'HiddenSignals: Implicit Suicidal Ideation Dataset'
+size_categories:
+- 1K<n<10K
+---