# tèmítáyò! (@theidealnurse__) on x

- id: koinon:creator:x_theidealnurse__
- url: https://koinonlink.com/kol/x/theidealnurse__
- schema_version: 1.4

## Identity
- platform: x
- handle: theidealnurse__
- platform_url: https://twitter.com/theidealnurse__
- website: http://www.theidealnurse.wordpress.com
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 1738
- following: 1032
- posts_total: 18914
- posts_observed: 1
- posts_per_day: 4.659
- account_age_days: 4060
- verified: false
- size_tier: nano

## Engagement
- status: not_collected
- status_note: Engagement has not been collected for this creator yet. This is a gap in our collection, NOT a statement that the creator has no engagement. Follower count is known, so it is measurable.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: software
- subcategory: ai_tools
- category_confidence: 0.6
- category_source: derived_from_discovery_path
- topics: HMO policies and healthcare financing, Accountability in hospital systems, Patient vs systemic blame, Nursing professional challenges
- bio: ¡Pura vida! PM👩‍💻 and Goldsmith @kostumbyteeta🛠️
Building @NursesHaven one day at a time💙

## Audience (inferred)
- status: present
- description: Nigerian nurses and frontline healthcare workers discussing HMO policies, hospital systems, and patient care issues
- roles: none
- seniority: practitioner
- pain_points: HMO non-payment and abuse leading to financial strain on hospitals, Patients being unfairly blamed instead of fixing systemic problems, Overload from unrestricted access without proper accountability, Lack of clear responsibility between HMOs, hospitals, and staff
- posts_analysed: 7
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.2
- promotion_intent: 0.1
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 45
- authenticity_basis: profile_shape_only
- credibility_score: 45
- flagged_for_review: false
- koinon_bd_grade: C — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [x_theidealnurse__#14b4c409] Na me and @Motushbae that year. 🤭 (https://twitter.com/theidealnurse__/status/2072972921690034354)
- [x_theidealnurse__#e104956e] 😂😂😂
- [x_theidealnurse__#3fcaa8ac] Some are saying it’s all a joke, some are doubling down, some are saying it is HMO abuse. At the end of the day, everybody knows exactly what they’re doing.
- [x_theidealnurse__#5a028acb] It’s sha not the patient’s problem. Make una sort una selves or educate them on what to do instead.
- [x_theidealnurse__#f10ede75] Exactly. Systems not the people.
- [x_theidealnurse__#8e118d98] You’d rather stay fresh for next emergency and shame them for coming out n matching Ankara but you forget that the same headache you didn’t want to attend to last month could be the reason for the next emergency.😌🤔
- [x_theidealnurse__#6a919087] My opinion because if HMOs sell unrestricted access and the hospitals agreed to it, the patients are not to blame, imo. Everybody should own their own part and do the needful. https://t.co/1uljpfZFw1
- [x_theidealnurse__#0203ab81] My own is that if out of pocket patients come for same complaints, would it be acceptable? If yes, uhm. Also, if HMO doesn't pay during

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=87, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=87, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=87, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=87, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=87, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=120, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.25, freshness_days=87, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=120, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=120, method=platform_profile

## Freshness
- profile_checked_days_ago: 120
- content_analysed_days_ago: 87
- audience_updated_days_ago: 87

## AI retrieval
- indexing_requests: 5
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=x_theidealnurse__
- Request removal: https://koinonlink.com/claim?k=x_theidealnurse__
- Terms: https://koinonlink.com/for-ai