Remove livestock category: images don't match the label, flag was text-derived not image-derived

README.md

@@ -9,40 +9,48 @@ language:
 task_categories:
 - image-classification
 - tabular-classification
-pretty_name: FarmerChat Crop and Livestock Image Samples
+pretty_name: FarmerChat Crop Image Samples
 size_categories:
 - 1K<n<10K
 tags:
 - agriculture
 - plant-disease
 - crop-health
-- livestock
 - india
 - africa
 - multilingual
 ---
 
-# FarmerChat Crop and Livestock Image Samples
+# FarmerChat Crop Image Samples
 
 A sample of farmer-submitted photographs from FarmerChat, an agricultural advisory service
 used by smallholder farmers in India, Ethiopia, Kenya and Nigeria. Published by
 [Digital Green](https://www.digitalgreen.org).
 
-This release contains 6,066 records (5,930 distinct photographs; some
-photographs belong to more than one category, see below) drawn from 7 categories
-representing different outcomes of an automated crop/livestock diagnosis pipeline, sampled
+This release contains 5,946 records (5,814 distinct photographs; some
+photographs belong to more than one category, see below) drawn from 6 categories
+representing different outcomes of an automated crop diagnosis pipeline, sampled
 across country, month, crop and diagnosis where each applies.
 
 Submissions span 2025-08 to 2026-07.
 
 ## Changes in this version
 
-This version replaces an earlier release that had two problems: some images had never
-actually cleared the service's quality gate (most notably in the livestock category), and
-a small number of off-topic images (screenshots, AI-generated pictures) had slipped
-through because the quality gate only checks blur/framing, not content. Both are fixed
-here — see "How these images were selected" below — which is why the record count and
-category sizes differ from the previous version.
+This version replaces an earlier release that had three problems. Some images had never
+actually cleared the service's quality gate. A small number of off-topic images
+(screenshots, AI-generated pictures) had slipped through because the quality gate only
+checks blur/framing, not content — both fixed, see "How these images were selected" below.
+
+Third, the `livestock` category has been removed entirely. It was built from
+`livestock_signal`, a flag derived from the farmer's accompanying text, not from the
+photo — and on inspection, none of its images actually showed an animal (they were plant
+photos sent alongside a livestock-related question, or otherwise mismatched). The
+automated content check in step 2 below does not catch this: it verifies a photo is a
+real, on-topic agricultural image, not that it matches its assigned category, so these
+rows passed it cleanly despite being wrongly categorized. Rather than publish a category
+that doesn't reliably contain what it claims to, it's cut until we have a livestock-photo
+label that's actually image-derived. This is why the record count and category count both
+dropped again from the previous version of this fix.
 
 ## Loading
 
@@ -70,26 +78,22 @@ Every photograph in this release cleared two independent screens.
 Farmers do send off-topic images to the service — screenshots, photos of documents, pets,
 food, AI-generated pictures. Those are a real and interesting property of the traffic, but
 they are filtered out here so this dataset is what it claims to be: real photographs of
-crops and livestock.
+crops.
 
 ## Categories
 
 | Category | Records | What it represents |
 |---|---:|---|
+| `multimodal_organic_text` | 999 | The photograph was accompanied by farmer-written text (not a repeated quick-reply template) |
+| `low_confidence_diagnosis` | 995 | A diagnosis was returned, but with lower model confidence |
 | `diagnosis_returned` | 991 | A crop was identified and a specific disease/pest diagnosis was returned |
 | `crop_identified_diagnosis_unresolved` | 991 | A crop was identified but the health outcome was not determined |
-| `crop_unresolved` | 983 | No crop could be identified in the photograph |
 | `healthy_crop` | 987 | A crop was identified and assessed as healthy |
-| `low_confidence_diagnosis` | 995 | A diagnosis was returned, but with lower model confidence |
-| `livestock` | 120 | The submission was flagged as livestock-related rather than crop-related |
-| `multimodal_organic_text` | 999 | The photograph was accompanied by farmer-written text (not a repeated quick-reply template) |
-
-An image can belong to more than one category (for example, a livestock photo with a
-low-confidence diagnosis). Each membership is its own row in `metadata.csv`, sharing the
-same `file_name`.
+| `crop_unresolved` | 983 | No crop could be identified in the photograph |
 
-Category sizes are uneven. `livestock` is much smaller than the others because most
-livestock-related submissions do not clear the image-quality gate.
+An image can belong to more than one category (for example, a low-confidence diagnosis
+photo that also arrived with organic farmer text). Each membership is its own row in
+`metadata.csv`, sharing the same `file_name`.
 
 ## Columns
 
@@ -102,7 +106,6 @@ livestock-related submissions do not clear the image-quality gate.
 | `month` | Year-month the photo was submitted (YYYY-MM) |
 | `crop` | Crop identified in the photo, where resolved. Normalized to a standard set of names (synonyms merged, casing standardized) |
 | `diagnosis` | Diagnosis identified, where resolved. Normalized the same way — not a pass-through of any single service's raw label |
-| `livestock_signal` | `Yes` / `No` / `Unknown` — whether the submission was flagged as livestock-related |
 | `query_present` | Whether the farmer sent text alongside the photo |
 | `farmer_query` | Farmer's question, in the original language, PII-redacted |
 | `farmer_query_en` | The same question translated to English, PII-redacted |