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Class: HumanSubjectCompensation

What participants received, and — where the sources describe one — how that was structured to keep them enrolled.

Two different claims live here and must not be conflated (#504). Compensation is payment for time and burden: what was provided, of what type, of what value. Retention incentives are structure designed to prevent attrition — escalating amounts, completion bonuses, payments tied to later visits. The ethical reading of the two differs, which is why an Ethics and Privacy review asked for the distinction: "$40 then $80" reported as compensation says something different from the same figures reported as a retention design.

Record the incentive slots only where a source describes the structure or its purpose. Most sources describe payments and say nothing about retention intent, and an escalating schedule is not by itself evidence that retention was the goal. Inferring one from the other is the failure the evidence boundary exists to prevent.

__

URI: data_sheets_schema:HumanSubjectCompensation

classDiagram class HumanSubjectCompensation click HumanSubjectCompensation href "../HumanSubjectCompensation/" DatasetProperty <|-- HumanSubjectCompensation click DatasetProperty href "../DatasetProperty/" HumanSubjectCompensation : compensation_amount HumanSubjectCompensation : compensation_provided HumanSubjectCompensation : compensation_rationale HumanSubjectCompensation : compensation_type HumanSubjectCompensation : description HumanSubjectCompensation : id HumanSubjectCompensation : name HumanSubjectCompensation : notes HumanSubjectCompensation : retention_incentive_rationale HumanSubjectCompensation : retention_incentives HumanSubjectCompensation : source_caveats HumanSubjectCompensation : used_software HumanSubjectCompensation --> "*" Software : used_software click Software href "../Software/"

Inheritance

Slots

Name Cardinality and Range Description Inheritance
compensation_provided 0..1
Boolean		 Were participants compensated for their participation? direct
compensation_type 0..1
String		 What type of compensation was provided (e direct
compensation_amount 0..1
String		 What was the amount or value of compensation provided? Include currency or eq... direct
compensation_rationale 0..1
String		 What was the rationale for the compensation structure? How was the amount det... direct
retention_incentives 0..1
String		 Where the sources describe it, how the incentive structure was designed to ke... direct
retention_incentive_rationale 0..1
String		 The stated reason for structuring incentives to support retention, where a so... direct
id 0..1
Uriorcurie		 An optional identifier for this property DatasetProperty
name 0..1
String		 A human-readable name for this property DatasetProperty
description 0..1
String		 A human-readable description for this property DatasetProperty
notes 0..1
String		 Residual content only, after every fitting slot is used (#385): structured sl... DatasetProperty
source_caveats 0..1
String		 Commentary on the evidence behind this object's values — source conflicts, wh... DatasetProperty
used_software *
Software		 What software was used as part of this dataset property? DatasetProperty

Usages

used by used in type used
Dataset participant_compensation range HumanSubjectCompensation
DataSubset participant_compensation range HumanSubjectCompensation

Identifier and Mapping Information

Schema Source

  • from schema: https://w3id.org/bridge2ai/data-sheets-schema

Mappings

Mapping Type Mapped Value
self data_sheets_schema:HumanSubjectCompensation
native data_sheets_schema:HumanSubjectCompensation

LinkML Source

Direct

name: HumanSubjectCompensation
description: 'What participants received, and — where the sources describe one — how
  that was structured to keep them enrolled.

  Two different claims live here and must not be conflated (#504). **Compensation**
  is payment for time and burden: what was provided, of what type, of what value.
  **Retention incentives** are structure designed to prevent attrition — escalating
  amounts, completion bonuses, payments tied to later visits. The ethical reading
  of the two differs, which is why an Ethics and Privacy review asked for the distinction:
  "$40 then $80" reported as compensation says something different from the same figures
  reported as a retention design.

  Record the incentive slots only where a source describes the structure or its purpose.
  Most sources describe payments and say nothing about retention intent, and an escalating
  schedule is not by itself evidence that retention was the goal. Inferring one from
  the other is the failure the evidence boundary exists to prevent.

  '
from_schema: https://w3id.org/bridge2ai/data-sheets-schema
is_a: DatasetProperty
attributes:
  compensation_provided:
    name: compensation_provided
    description: Were participants compensated for their participation?
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:compensationProvided
    domain_of:
    - HumanSubjectCompensation
    range: boolean
  compensation_type:
    name: compensation_type
    annotations:
      d4d:docExample:
        tag: d4d:docExample
        value: Monetary payment via gift card
    description: 'What type of compensation was provided (e.g., monetary payment,
      gift cards, course credit, other incentives)?

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:compensationType
    domain_of:
    - HumanSubjectCompensation
    range: string
  compensation_amount:
    name: compensation_amount
    annotations:
      d4d:docExample:
        tag: d4d:docExample
        value: $75 for initial visit; $25 for annual follow-up
    description: 'What was the amount or value of compensation provided? Include currency
      or equivalent value.

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:compensationAmount
    domain_of:
    - HumanSubjectCompensation
    range: string
  compensation_rationale:
    name: compensation_rationale
    description: 'What was the rationale for the compensation structure? How was the
      amount determined to be appropriate?

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:compensationRationale
    domain_of:
    - HumanSubjectCompensation
    range: string
  retention_incentives:
    name: retention_incentives
    annotations:
      d4d:docExample:
        tag: d4d:docExample
        value: Payment rises across the annual visits, with a completion bonus at
          the final visit, described in the protocol as designed to reduce loss to
          follow-up.
    description: 'Where the sources describe it, how the incentive structure was designed
      to keep participants enrolled across the study — escalating amounts, completion
      bonuses, payments tied to later visits or to returning after a gap.

      Distinct from `compensation_type` and `compensation_amount`, which record what
      was provided. State this only where a source describes the structure. An escalating
      payment schedule is not by itself evidence that retention was its purpose; report
      the schedule under the compensation slots and leave this absent.

      ⚠️ **"Retention" here means keeping participants enrolled, never keeping data.**
      How long the data is kept belongs in `retention_limit`, which is a different
      slot about a different subject. The word is treacherous in this corpus: across
      all five project bundles nearly every occurrence of "retention" is about data
      or specimen retention — "limits on the retention of the data", "bioSpecRetention",
      "records retention requirements" — and none so far describes an incentive structure.
      An empty slot is the correct outcome for those sources.

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:retentionIncentiveStructure
    domain_of:
    - HumanSubjectCompensation
    range: string
  retention_incentive_rationale:
    name: retention_incentive_rationale
    description: 'The stated reason for structuring incentives to support retention,
      where a source gives one — an attrition rate the design responds to, an IRB
      condition, or a documented equity concern about who can afford to stay enrolled.

      Separate from `retention_incentives` (the structure) for the same reason `compensation_rationale`
      is separate from `compensation_amount`: what was done and why it was done are
      different claims, and sources frequently give one without the other.

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:retentionIncentiveRationale
    domain_of:
    - HumanSubjectCompensation
    range: string

Induced

name: HumanSubjectCompensation
description: 'What participants received, and — where the sources describe one — how
  that was structured to keep them enrolled.

  Two different claims live here and must not be conflated (#504). **Compensation**
  is payment for time and burden: what was provided, of what type, of what value.
  **Retention incentives** are structure designed to prevent attrition — escalating
  amounts, completion bonuses, payments tied to later visits. The ethical reading
  of the two differs, which is why an Ethics and Privacy review asked for the distinction:
  "$40 then $80" reported as compensation says something different from the same figures
  reported as a retention design.

  Record the incentive slots only where a source describes the structure or its purpose.
  Most sources describe payments and say nothing about retention intent, and an escalating
  schedule is not by itself evidence that retention was the goal. Inferring one from
  the other is the failure the evidence boundary exists to prevent.

  '
from_schema: https://w3id.org/bridge2ai/data-sheets-schema
is_a: DatasetProperty
attributes:
  compensation_provided:
    name: compensation_provided
    description: Were participants compensated for their participation?
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:compensationProvided
    alias: compensation_provided
    owner: HumanSubjectCompensation
    domain_of:
    - HumanSubjectCompensation
    range: boolean
  compensation_type:
    name: compensation_type
    annotations:
      d4d:docExample:
        tag: d4d:docExample
        value: Monetary payment via gift card
    description: 'What type of compensation was provided (e.g., monetary payment,
      gift cards, course credit, other incentives)?

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:compensationType
    alias: compensation_type
    owner: HumanSubjectCompensation
    domain_of:
    - HumanSubjectCompensation
    range: string
  compensation_amount:
    name: compensation_amount
    annotations:
      d4d:docExample:
        tag: d4d:docExample
        value: $75 for initial visit; $25 for annual follow-up
    description: 'What was the amount or value of compensation provided? Include currency
      or equivalent value.

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:compensationAmount
    alias: compensation_amount
    owner: HumanSubjectCompensation
    domain_of:
    - HumanSubjectCompensation
    range: string
  compensation_rationale:
    name: compensation_rationale
    description: 'What was the rationale for the compensation structure? How was the
      amount determined to be appropriate?

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:compensationRationale
    alias: compensation_rationale
    owner: HumanSubjectCompensation
    domain_of:
    - HumanSubjectCompensation
    range: string
  retention_incentives:
    name: retention_incentives
    annotations:
      d4d:docExample:
        tag: d4d:docExample
        value: Payment rises across the annual visits, with a completion bonus at
          the final visit, described in the protocol as designed to reduce loss to
          follow-up.
    description: 'Where the sources describe it, how the incentive structure was designed
      to keep participants enrolled across the study — escalating amounts, completion
      bonuses, payments tied to later visits or to returning after a gap.

      Distinct from `compensation_type` and `compensation_amount`, which record what
      was provided. State this only where a source describes the structure. An escalating
      payment schedule is not by itself evidence that retention was its purpose; report
      the schedule under the compensation slots and leave this absent.

      ⚠️ **"Retention" here means keeping participants enrolled, never keeping data.**
      How long the data is kept belongs in `retention_limit`, which is a different
      slot about a different subject. The word is treacherous in this corpus: across
      all five project bundles nearly every occurrence of "retention" is about data
      or specimen retention — "limits on the retention of the data", "bioSpecRetention",
      "records retention requirements" — and none so far describes an incentive structure.
      An empty slot is the correct outcome for those sources.

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:retentionIncentiveStructure
    alias: retention_incentives
    owner: HumanSubjectCompensation
    domain_of:
    - HumanSubjectCompensation
    range: string
  retention_incentive_rationale:
    name: retention_incentive_rationale
    description: 'The stated reason for structuring incentives to support retention,
      where a source gives one — an attrition rate the design responds to, an IRB
      condition, or a documented equity concern about who can afford to stay enrolled.

      Separate from `retention_incentives` (the structure) for the same reason `compensation_rationale`
      is separate from `compensation_amount`: what was done and why it was done are
      different claims, and sources frequently give one without the other.

      '
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/human
    rank: 1000
    slot_uri: d4d:retentionIncentiveRationale
    alias: retention_incentive_rationale
    owner: HumanSubjectCompensation
    domain_of:
    - HumanSubjectCompensation
    range: string
  id:
    name: id
    annotations:
      d4d:docExample:
        tag: d4d:docExample
        value: https://example.org/dataset/property-001
    description: An optional identifier for this property.
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/base
    slot_uri: schema:identifier
    alias: id
    owner: HumanSubjectCompensation
    domain_of:
    - NamedThing
    - Organization
    - DatasetProperty
    - Grant
    range: uriorcurie
  name:
    name: name
    description: A human-readable name for this property.
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/base
    slot_uri: schema:name
    alias: name
    owner: HumanSubjectCompensation
    domain_of:
    - NamedThing
    - Organization
    - DatasetProperty
    - Grant
    range: string
  description:
    name: description
    description: A human-readable description for this property.
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/base
    slot_uri: schema:description
    alias: description
    owner: HumanSubjectCompensation
    domain_of:
    - NamedThing
    - Organization
    - DatasetProperty
    - Grant
    - DatasetRelationship
    range: string
  notes:
    name: notes
    description: 'Residual content only, after every fitting slot is used (#385):
      structured slots first, description as the default home for narrative, notes
      last — solely for content description cannot hold. Never a restatement of a
      sibling slot''s value, and never a substitute for inventing keys the schema
      does not declare (#380).'
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/base
    slot_uri: schema:comment
    alias: notes
    owner: HumanSubjectCompensation
    domain_of:
    - NamedThing
    - Organization
    - DatasetProperty
    - Grant
    range: string
  source_caveats:
    name: source_caveats
    description: 'Commentary on the evidence behind this object''s values — source
      conflicts, what a value was transcribed from, questions the source material
      leaves unanswered (#385). A trust annotation about the sibling slots, not dataset
      content: content belongs in the structured slots, description or notes.'
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/base
    slot_uri: dcterms:provenance
    alias: source_caveats
    owner: HumanSubjectCompensation
    domain_of:
    - NamedThing
    - Organization
    - DatasetProperty
    - Grant
    range: string
  used_software:
    name: used_software
    description: What software was used as part of this dataset property?
    from_schema: https://w3id.org/bridge2ai/data-sheets-schema/base
    rank: 1000
    slot_uri: d4d:usedSoftware
    alias: used_software
    owner: HumanSubjectCompensation
    domain_of:
    - DatasetProperty
    range: Software
    multivalued: true
    inlined: true
    inlined_as_list: true